This page tracks remote data engineer openings that are location-eligible for Missouri.
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• Design and develop Power BI dashboards and reports that support school operations, student outcomes analysis, and enterprise reporting • Translate business needs into intuitive, actionable visualizations aligned with PVS reporting standards • Optimize report performance, usability, and accessibility for diverse end users (school leaders, analysts, executives) • Implement and maintain data security policies within reporting tools in adherence with PVS data security policies, governance and best practices • Build and maintain Power BI semantic models (datasets) that serve as governed, reusable data foundations • Implement data modeling best practices (star schema, DAX optimization, row-level security) • Partner with engineering to ensure alignment between data pipelines and reporting layer • Validate data outputs and ensure consistency between reports and source systems • Troubleshoot data discrepancies, refresh failures, and performance issues • Contribute to monitoring, testing, and documentation of reporting solutions • Implement and validate Row Level Security in a multi-tenant environment • Work closely with business stakeholders to refine requirements and prioritize features • Participate in design discussions, backlog refinement, and peer reviews • Communicate technical tradeoffs, risks, and timelines clearly to both technical and non-technical audiences • Contribute to the development of scalable, reusable reporting assets that align with PVS data product strategy • Support self-service analytics by enabling well-documented datasets and consistent definitions • Drive improvements in deployment practices, governance, and lifecycle management
Role Description We are looking for a highly skilled and experienced L2 Data Engineer to join our growing Data & Analytics team. In this role, you will lead the design, development, optimization, and maintenance of scalable enterprise data platforms and cloud-native data solutions. You will work closely with architects, analysts, and business stakeholders to build high-performance data pipelines and modern lakehouse solutions that support advanced analytics, reporting, and data-driven decision-making. This opportunity is ideal for a senior data professional with strong hands-on expertise in Databricks and the Microsoft Azure ecosystem, who is passionate about building reliable, scalable, and optimized data platforms in enterprise environments. Qualifications - 5+ years of professional experience in Data Engineering or related roles. - Strong expertise in Python for enterprise data processing, transformation, and automation. - Advanced hands-on experience with Pandas, PySpark, and Spark SQL for large-scale distributed processing. - Strong experience with Databricks, including cluster management, notebook development, workflow orchestration, Delta Lake, and performance optimization. - Extensive experience building and managing enterprise data pipelines using Azure Data Factory. - Strong working knowledge of Azure Synapse Analytics, particularly Spark pool integration and enterprise data warehousing concepts. - Advanced SQL skills including query optimization, performance tuning, indexing strategies, and troubleshooting. - Strong understanding of data lake architecture, Delta Lake, incremental processing, partitioning, and lakehouse concepts. - Experience implementing data governance, security, access controls, and monitoring within cloud data platforms. - Experience handling production support, troubleshooting, and optimization of enterprise data platforms. Requirements - Design, develop, and optimize enterprise-scale data pipelines and ETL/ELT workflows using Azure and Databricks technologies. - Architect and implement scalable data ingestion, transformation, and orchestration processes using Azure Data Factory, Databricks, and Azure Synapse Analytics. - Develop high-performance data transformation frameworks using PySpark, Python, and Spark SQL for large-scale distributed data processing. - Optimize SQL queries, Spark jobs, and data workflows to improve performance, scalability, and cost efficiency. - Lead data migration initiatives, including SQL Server migrations and modernization of legacy data platforms. - Implement and maintain Delta Lake architecture, incremental data loading strategies, and enterprise data lake best practices. - Collaborate with architects and cross-functional teams to design robust and scalable data models aligned with business and governance standards. - Monitor and troubleshoot production pipelines, perform root-cause analysis, and implement preventive measures for recurring issues. - Support CI/CD implementation and infrastructure automation for data engineering workflows. - Mentor junior engineers and contribute to engineering standards, reusable frameworks, and technical best practices. - Create and maintain technical documentation including architecture diagrams, pipeline documentation, and operational runbooks. - Evaluate and recommend modern data engineering tools, frameworks, and optimization strategies. Benefits - Experience with Terraform for Azure infrastructure provisioning and Infrastructure-as-Code (IaC). - Experience implementing CI/CD pipelines for data engineering deployments. - Exposure to Lakehouse Federation, Delta Sharing, and modern data sharing architectures. - Experience with streaming and near real-time data processing solutions. - Knowledge of DevOps practices and cloud cost optimization strategies. Certification Requirement Candidates are expected to hold or be actively working toward the Databricks Certified Data Engineer Professional certification. This certification validates advanced expertise across the following domains: - Advanced ETL and ELT development using Spark SQL and PySpark - Enterprise-grade pipeline orchestration and optimization - Data modeling and scalable lakehouse architecture - Performance tuning and distributed data processing optimization - Advanced data governance and security implementation - Production-grade data engineering practices within the Databricks ecosystem
Role Description We are looking for a Middle Data Engineer specialized in Azure Databricks to join our data platform team. The candidate will design and develop modern data pipelines and Lakehouse architectures, leveraging Azure Databricks, Spark, and Azure Data Factory, while integrating with existing SQL Server-based data warehouse environments, also evolving our data platform towards scalable, cloud-based data architectures, enabling advanced analytics and business intelligence. - Design, develop, and maintain data pipelines using Azure Databricks - Build and optimize data transformations using PySpark and SQL in Databricks - Implement and maintain Lakehouse architectures using Delta Lake - Develop ETL/ELT pipelines orchestrated through Azure Data Factory - Integrate data from multiple sources into the data platform and analytical layers - Design and maintain data models and data warehouse structures for analytics - Ensure data quality, scalability, and performance of large-scale data processing pipelines - Collaborate with BI teams to support Power BI and reporting platforms - Support and evolve existing SQL Server data platforms and ETL solutions (SSIS) when required - Contribute to the design of modern cloud-based data architectures Qualifications - 3+ years of experience in Data Engineering or Data Warehouse development - Strong experience with Azure Databricks - Experience developing data pipelines using PySpark and Spark SQL - Solid understanding of distributed data processing and big data concepts - Experience working with Delta Lake and Lakehouse architectures - Strong SQL skills and experience with SQL Server relational databases - Experience building data pipelines using Azure Data Factory - Experience handling large datasets and performance optimization Requirements - Experience with Spark optimization techniques (partitioning, caching, cluster tuning) - Experience with structured streaming in Databricks - Knowledge of CI/CD pipelines for data platforms (Azure Devops) - Familiarity with Power BI - Experience in migrating from traditional ETL process to cloud architectures Benefits - Culture of Relentless Performance: join an unstoppable technology development team with a 99% project success rate and more than 30% year-over-year revenue growth. - Competitive Pay and Benefits: enjoy a comprehensive compensation and benefits package, including health insurance, and a relocation program. - Work From Anywhere Culture: make the most of the flexibility that comes with remote work. - Growth Mindset: reap the benefits of a range of professional development opportunities, including certification programs, mentorship and talent investment programs, internal mobility and internship opportunities. - Global Impact: collaborate on impactful projects for top global clients and shape the future of industries. - Welcoming Multicultural Environment: be a part of a dynamic, global team and thrive in an inclusive and supportive work environment with open communication and regular team-building company social events. - Social Sustainability Values: join our sustainable business practices focused on five pillars, including IT education, community empowerment, fair operating practices, environmental sustainability, and gender equality.
One-stop-shop for entrepreneurs to start & grow their business in Australia, Hong Kong, Singapore and the UK.
Role Description We are looking for a skilled and passionate Data Engineer to join our growing Data Platform team. Mission: - Design, build, and maintain robust data pipelines on Databricks and AWS infrastructure that power analytics and reporting capabilities across the organization. Key responsibilities: - Design and implement scalable ETL/ELT pipelines using both batch and streaming patterns. - Build and maintain ingestion workflows from diverse sources (databases, APIs, event streams). - Implement Change Data Capture (CDC), full-load, and incremental ingestion strategies. - Develop and manage data workflows using Apache Airflow for orchestration. - Configure and manage data ingestion connectors using Airbyte. - Work with Databricks to build and optimize data engineering workloads on the Lakehouse platform. - Write and optimize complex SQL queries. - Solid hands-on experience on dbt with Databricks, build modular, testable dbt models for data transformation. - Develop and maintain data models in staging, intermediate, and mart layers following data warehousing best practices. - Working knowledge of AWS services like S3, Lambda, EC2, IAM, etc. - Containerize data services and applications using Docker & EKS. - Ensure data quality, observability, and reliability across the data platform. - Document pipelines, models, and data dictionaries to maintain platform knowledge. Qualifications - 3+ years of professional experience in data engineering. - Strong understanding of data platform architecture: Lakehouse, Data Warehouse, Data Lake patterns. - Hands-on experience with ETL/ELT design patterns including batch processing and stream processing. - Familiarity with ingestion patterns: full load, incremental, CDC, event-driven. - 5+ years of hands-on experience as a Database Administrator in production environments. - Strong understanding of database internals — storage engines, transactions, isolation levels, locking, MVCC, query planners. - Proven experience supporting mission-critical OLTP workloads with high availability requirements. - Solid scripting skills in Bash and/or Python for automation. Requirements - Experience building data pipelines on Databricks (Delta Live Tables, Jobs, Notebooks). - Proficiency with PySpark or Spark SQL for large-scale data processing. - Familiarity with Delta Lake concepts: ACID transactions, time travel, schema evolution. - Proficiency with Apache Airflow — authoring, scheduling, and monitoring DAGs. - Experience with Airbyte for managing source-to-destination data connectors. - Hands-on experience administering MongoDB (self-managed and/or Atlas). - Replica set configuration, sharding, indexing strategies, and aggregation pipeline tuning. - Backup, restore, and disaster recovery using mongodump/mongorestore or Ops Manager. - Strong SQL skills — query optimization, window functions, CTEs, and complex joins. - Experience with dbt (data build tool) for transformation, testing, and documentation. - Practical experience with AWS services (S3, Lambda, IAM, CloudWatch, etc). Benefits - Humility and kindness: A culture of not taking ourselves too seriously and being able to laugh. - Flexibility: Work from home and the option to work fully remote from anywhere in the world for 1 month each year. - Financial benefits: Competitive market salaries, generous paid time off, and access to a flexi benefits scheme. - Personal growth: Responsibility and autonomy with a range of internal and external training programs. Company Description Sleek launched in 2017 and now has around 15,000 customers across our offices in Singapore, Hong Kong, Australia, and the UK. We have around 500 staff with an intact startup mindset. We have recently raised Series B financing off the back of >70% compound annual growth in Revenue over the last 5 years. Sleek has been recognised by The Financial Times, The Straits Times, Forbes, and LinkedIn as one of the fastest-growing companies in Asia. Backed by world-class investors, we are on track to be one of the few cash flow positive, tech-enabled unicorns based out of Asia Pacific.
Founded in 2007, GTech is a consulting services firm passionate about delivering tailored solutions that meet our clients' needs and maximize the value of their investments. Our team embodies integrity, commitment, and reliability, which are at the heart of everything we do. We are dedicated to fostering a culture of support for our employees—the lifeblood of our business. At Graham Technologies, we've built a family-oriented environment where team members are encouraged to maintain a healthy work-life balance, pursue their passions, and grow professionally through flexible schedules, continued education, and a strong sense of community.
Role Description Graham Technologies is seeking a highly skilled Data Engineer. This role will focus on designing, implementing, and optimizing cloud-native data pipelines, governance frameworks, AI-ready infrastructure, and enterprise data platforms supporting our customers' mission objectives. The ideal candidate will possess strong cloud engineering, ETL/ELT, data governance, and analytics expertise with experience supporting large-scale scientific or federal data environments. Location: Remote Key Responsibilities: - Collaborate with customer data practitioners and IT staff to develop cloud infrastructure requirements - Analyze technical options and develop cloud architecture proposals for modernization initiatives - Design, build, and maintain scalable ETL/ELT pipelines supporting structured and unstructured datasets - Implement Infrastructure-as-Code (IaC) automation and deployment workflows - Develop data ingestion, transformation, metadata management, and reporting solutions - Support governance standards, data quality frameworks, and enterprise metadata harvesting - Enable AI/ML and MLOps lifecycle infrastructure across NOS programs - Support GIS, video, analytics, and environmental data systems modernization efforts - Develop operational reporting, performance metrics, and compliance dashboards - Collaborate with cross-functional technical and non-technical stakeholders - Provide monthly status reporting and support quarterly stakeholder reviews - Support customer-wide data management initiatives and emerging mission programs Qualifications - Minimum 7+ years of experience in data engineering, cloud infrastructure, or enterprise data management - Experience designing and implementing ETL/ELT pipelines and enterprise data warehouses - Experience with cloud-native architectures and distributed data processing frameworks - Experience supporting large-scale data modernization initiatives - Experience with metadata management, data governance, and data quality processes - Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related technical field - Experience with cloud platforms such as AWS, Azure, or Google Cloud - Experience with Infrastructure-as-Code tools such as Terraform or CloudFormation - Experience with SQL, Python, and enterprise data integration tools - Familiarity with Kubernetes, containerization, and CI/CD pipelines preferred - Experience with GIS and geospatial technologies preferred - Strong analytical and problem-solving abilities - Excellent written and verbal communication skills - Ability to communicate complex technical concepts to diverse stakeholders - Strong project coordination and prioritization capabilities - Ability to work independently within distributed remote teams Requirements - Federal Government program support experience - Experience supporting AI/ML infrastructure and MLOps environments - Experience with environmental, scientific, or geospatial datasets - Experience supporting enterprise analytics and reporting platforms - Master's degree in Data Science, Computer Science, Engineering, or related discipline - Ability to obtain and maintain a Public Trust or other Government suitability requirements - Controlled Unclassified Information (CUI) handling procedures - Federal cloud modernization and governance frameworks Benefits - Four Weeks of Accrued PTO in the First Year - Eleven Paid Federal Holidays - Comprehensive Health, Dental, Vision, and Life Insurance - 401(k) Plan with Annual Employer Contributions - Flexible Schedules - Reimbursements for Continued Education and Training Company Description Founded in 2007, GTech is a consulting services firm passionate about delivering tailored solutions that meet our clients' needs and maximize the value of their investments. Our team embodies integrity, commitment, and reliability, which are at the heart of everything we do. We are also dedicated to fostering a culture of support for our employees—the lifeblood of our business. At Graham Technologies, we've built a family-oriented environment where team members are encouraged to maintain a healthy work-life balance, pursue their passions, and grow professionally through flexible schedules, continued education, and a strong sense of community.
It’s no secret that our associates love #LifeAtKohls and we know you will too.
Role Description As Senior Data Engineer, you will lead the development and ownership of domain data products, including batch, streaming and artificial intelligence/machine learning (AI/ML) feature pipelines. You will drive design decisions that improve data reliability, performance and governance maturity while standardizing patterns that scale across teams. You will partner cross-functionally to enable analytics, ML and GenAI use cases with trusted data. - Design, build and maintain batch, streaming and real-time Artificial Intelligence (AI) feature pipelines to extract data from diverse source systems and producers (APIs, events, databases, files) ensuring efficient ingestion, transformation and publishing. - Design, refine and implement scalable data models, semantic layers and data contracts to promote consistency, reuse and accessibility. - Own the end-to-end data product lifecycle for the domain. Define and maintain data contracts, including service level agreements (SLAs), schema expectations, quality metrics and consumer ownership, to ensure a reliable and trustworthy experience. - Partner with cross functional teams to co-design scalable data solutions that meet business needs and clearly define the boundaries between data pipeline responsibilities and model-building activities. - Develop automated workflows and Continuous Integration / Continuous Deployment (CI/CD) pipelines using tools such as Airflow, Apache Spark and Python to drive reliability and faster delivery. - Implement validation, observability and evaluation frameworks that ensure accuracy, lineage and timeliness across data pipelines and large language model (LLM) outputs. - Apply and enforce governance, privacy and compliance standards (GDPR, PCI DSS, CCPA), ensuring data security and traceability. - Partner with cross functional teams to translate business needs into technical data solutions that scale across domains. - Drive performance tuning, automation and adoption of AI-powered data tools to enhance data platform efficiency. - Mentor data engineers and champion best practices for maintainable, governed and reusable data assets. - Own cost and performance tradeoffs for domain data products and monitor compute usage, storage growth and unit cost to implement optimizations that reduce spend while meeting SLAs. - Additional tasks may be assigned. Qualifications - 4+ years designing, building and optimizing data pipelines and models in production, ideally within large-scale cloud environments. - Proficiency in SQL and Python (or Scala) for data development, testing and automation. Requirements - Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering or a related field (preferred). - Experience with Apache Spark (or equivalent) for large-scale data processing and performance optimization (preferred). - Experience using Airflow/Cloud Composer/Dagster for orchestration, transformation and CI/CD pipelines (preferred). - Experience with cloud warehouses/lakes (BigQuery, Redshift, Snowflake) and object storage (preferred). - Experience designing and optimizing streaming pipelines using Kafka, Pub/Sub, spark (preferred). - Strong understanding of dimensional modeling, normalization and schema design for analytics and GenAI integration into data products (preferred). - Experience with data testing, lineage, monitoring and observability frameworks to ensure data integrity and reliability (preferred). Benefits - Ability to perform the accountabilities listed in the “What You’ll Do” Section. - Ability to maintain prompt and regular attendance as set by the company. - Ability to work at least 8 hours per day, occasionally longer when necessary to meet business needs, 5 days per week. - Ability to comply with dress code requirements. - Ability to learn and comply with all company policies, procedures, standards and guidelines. - Ability to give direction and receive, understand and proactively respond to direction from leadership and other company personnel. - Ability to work as part of a team and interact effectively and appropriately with others. - Ability to maintain composure and work in a fast paced environment while accomplishing multiple tasks within established timeframes. - Ability to satisfactorily complete company training programs. - Perform work in accordance with the Physical/Cognitive Requirements section. Physical/Cognitive Requirements - Ability to use a personal computer for tasks such as communicating, preparing reports, etc. - Ability to plan, prioritize and monitor activities across business units. - Ability to complete or oversee the completion of assigned projects in a timely manner. - Ability to comply with health and safety standards.
Pinnacle Technical Resources, doing business as Pinnacle Group, provides workforce solutions and strategic services to companies in the staffing, project management, and IT consult
Title:Senior Data Engineer - ETL/SQL/Matillion Location: St. Louis, Missouri Job Description:: Duration: Contract Job ID: 177007 Job Overview: As a Senior Data Engineer, you will play a critical role in designing, building, and maintaining robust data pipelines and integration solutions to ensure seamless data flow across systems. You will work with a modern suite of cloud-based technologies, including Looker, Snowflake, Atlan, and Matillion, hosted in AWS. This position offers the opportunity to work fully remote from your home residence in one of the approved states. Join a team that fosters innovation, collaboration, and growth while driving smarter decision-making and scalable growth across the organization. Responsibilities: - Design, build, and maintain robust data pipelines and integration solutions. - Develop and optimize scalable ETL/ELT processes to drive innovation and business growth. - Create and maintain source-to-target mapping and detailed ELT documentation. - Analyze, map, and troubleshoot data across all stages of the ELT process. - Provide accurate estimates for ELT tasks and recommend process improvements. - Participate in production on-call support rotation for ETL processing. - Collaborate in a team-oriented environment and work independently as needed. - Incorporate security into all decisions and daily job responsibilities. Qualifications: - Must be authorized to work in the U.S. without sponsorship now or in the future. - Must reside in one of the approved states: AL, AZ, FL, GA, ID, IL (excludes Cook County), IA, IN, KS, KY, LA, MD, MI, MO, NV, NM, NC, OH, OK, PA, SC, TN, TX, UT, VA, WV, WI. - Ability to work within U.S. Central Standard Time core business hours. - 3+ years of hands-on experience with ETL for data integration and transformation. - 3+ years of experience writing and tuning complex SQLs, stored procedures, triggers, and functions. - 3+ years of experience in full lifecycle development, end-to-end testing, and data validation. - Experience with the Matillion platform. - Strong experience with AWS services, including Lambda functions and data pipeline orchestration. - Proven experience implementing Change Data Capture (CDC) strategies. Preferred: - Bachelor's degree in Computer Science, Computer Information Systems, Management Information Systems, Engineering, or a related field. - Experience with unit testing for ETL/ELT pipelines and data quality frameworks. - Strong ability to write complex queries and optimize for large-scale datasets. - Experience with job optimization and integration with CI/CD pipelines. - Ability to mentor junior engineers and lead small projects. - Experience in Agile/Scrum environments and familiarity with DevOps principles. About PTR Global: PTR Global is a leading provider of information technology and workforce solutions. PTR Global has become one of the largest providers in its industry, with over 5000 professionals providing services across the U.S. and Canada. For more information visit www.ptrglobal.com At PTR Global, we understand the importance of your privacy and security. We NEVER ASK job applicants to: - Pay any fee to be considered for, submitted to, or selected for any opportunity. - Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process. - Provide sensitive financial information such as credit card numbers or banking information. Successfully placed or hired candidates would only be asked for banking details after accepting an offer from us during our official onboarding processes as part of payroll setup. Pay Range: $60-65/Hr The specific compensation for this position will be determined by several factors, including the scope, complexity, and location of the role, as well as the cost of labor in the market; the skills, education, training, credentials, and experience of the candidate; and other conditions of employment. Our full-time consultants have access to benefits, including medical, dental, vision, and 401K contributions, as well as PTO, sick leave, and other benefits mandated by applicable state or localities where you reside or work. If you receive a suspicious message, email, or phone call claiming to be from PTR Global do not respond or click on any links. Instead, contact us directly at +1 214-740-2424. To report any concerns, please email us at legal@pinnacle1.com #LI-SA4
• Translate business requirements into data requests, reports and dashboards. • Strong Database & modeling concepts with exposure to SQL & NoSQL Databases • Strong data architecture patterns & principles, ability to design secure & scalable data lakes, data warehouse, data hubs, and other event-driven architectures • Expertise in designing and writing ETL processes in Python / Java / Scala • Understanding of Hadoop framework - Exposure to PySpark, Spark, Storm, HDFS, Hive • Strong hands-on experience with either Databricks or Snowflake; experience with both is desirable. • Knowledge of Master Data management and related tools • Strong exposure to data security and privacy regulations (GDPR, HIPAA) and best practices • Skilled in ensuring data accuracy, consistency, and quality • Experience with the AWS/Azure/GCP data engineering services • Knowledge of AWS services viz., AWS S3, Redshift, Lambda, DynamoDB, EMR, Glue, Lakeformation, Athena, Quicksight, RDS, Kinesis, Managed Kafka, API Gateway, CloudWatch • And / OR • Knowledge of Azure services viz., ADF, Data Catalog, Databricks, Azure Synapse Analytics, ADLS Gen2, Azure Devops • Ability to implement data validation processes and establish data quality standards. • Experience in Linux • Proficiency in data visualization tools like Tableau, Power BI or similar to create meaningful insights
The world's leading Aircraft Maintenance Tracking Solutions provider.
• Design, develop, and maintain high-performance, scalable, high-volume, and efficient ETL/ELT pipelines to extract, transform, and load data from various sources such as Oracle. • Create and optimize data models and schemas to support various use cases (such as AI/ML solutions, benchmarking, customer data delivery) in Snowflake and Redshift. • Ensure data quality, integrity/completeness, and governance by implementing best practices for monitoring and validation. • Build automated monitoring and alerting mechanisms. • Collaborate with cross-functional teams to understand data requirements to support business objectives. • Stay up to date with emerging trends and technologies in data engineering.
Founded in 1967, Capgemini is revered as one of the world's leading consulting, technology, and outsourcing agencies. In 2016 alone, the company reported global revenues of €12.5
Title: Lead Data Engineer Location: Irving United States Job Description: Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Location United States - Remote Your Role 10+ Years of Experience in Data Engineering• At least four years of experience designing and delivering data engineering solutions with Databricks - Ability to independently define and deploy an end to end data architecture that includes Databricks medallion architecture - Experience leading large teams of engineers and developers to deploy Databricks solutions - Expert level hands on development knowledge in PySpark/Python - Expert level hands on SQL development skills - Hands on cloud platform experience in two of the following cloud platforms: Azure, AWS, Google Cloud - Prior expertise deploying Delta Lake Solutions into production Required Skill and Expereince - Experience extracting value from large and complex sets of data from various sources and databases - Solid grasp of database engineering and design principles - Familiarity with CI/CD methods desired - Background working with orchestration tools, such as Airflow - Strong knowledge of Unity Catalog - Past or current experience with an ETL tools such as Infomatica, Talend, Matillion desired - Experienced in managing senior client stakeholders - Delta Sharing and Marketplace Expertise - Experience working with Databricks Apps - Working knowledge of Databricks Genie, AI/BI and Databricks Data Visualization Capabilities - Conceptual, Logical and The base compensation range for this role in the posted location is $90,000- $160,000 Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: - Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave - Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) - Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) - Life and disability insurance - Employee assistance programs - Other benefits as provided by local policy and eligibility Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation. Disclaimers Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process. Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
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ETL, SQL, Azure, Python, Data Engineering, CI/CD
