Role Description We are looking for a Data Engineer/ Data Modeler to support the design and implementation of a modern Azure-based data platform. The ideal candidate combines strong hands-on data engineering skills with the ability to work closely with business stakeholders, structure unclear requirements, and translate them into scalable data models. The role is especially suitable for someone with experience in: - Azure Synapse - Azure Data Factory - Python/ PySpark - SQL - SAP source systems - Data warehousing - Power BI reporting enablement Key Responsibilities - Analyze and clarify business requirements from scattered or incomplete documentation - Work directly with business departments to align requirements, data definitions, and reporting needs - Translate business requirements into conceptual, logical, and physical data models - Design and implement data models for: - Silver layer: normalized / 3NF model - Gold layer: dimensional / star schema model - Build and maintain medallion architecture in Azure Synapse, including silver and gold tables - Develop data transformations and pipelines using Azure Synapse, Azure Data Factory, SQL, Python/ PySpark - Integrate data mainly from SAP source systems - Support data cataloging, governance, and lineage through Microsoft Purview - Use Azure DevOps for repository management, CI/CD, and project tracking - Enable reporting and analytics through well-structured datasets for Power BI Qualifications - Strong experience with Azure cloud data platforms - Hands-on experience with: - Azure Synapse - Azure Data Factory - Python/ PySpark - SQL - Data Lake/ Lakehouse architectures - Solid understanding of data modeling: - 3NF / normalized models - Star schema/ dimensional modeling - Data warehouse design - Experience working with SAP source systems - Ability to translate business requirements into technical data models - Experience with Git-based development and CI/CD, ideally in Azure DevOps - Good understanding of reporting needs, ideally with Power BI - Strong communication skills and ability to work with both business and technical stakeholders Requirements - A significant advantage would be: - Experience with Microsoft Purview - Experience in enterprise reporting, forecasting, or analytics platforms - Background in SAP-heavy enterprise environments - Experience with agile delivery and tools such as Jira/ Azure DevOps - Microsoft data engineering certification is a plus Benefits - Diversity, equity and inclusion - Sustainability Additional Information At Tieto, we believe in the power of diversity, equity, and inclusion. We encourage applicants of all backgrounds, genders (m/f/d), and walks of life to join our team, as we believe that this fosters an inspiring workplace and fuels innovation. Our commitment to openness, trust, and diversity is at the heart of our mission to create digital futures that benefit businesses, societies, and humanity. Stay alert to recruitment scams: - Tieto only communicates via @tieto.com email addresses. - We never ask candidates to pay fees or share financial details during recruitment. - If you receive a suspicious message claiming to be from Tieto, don't respond — verify it via our official careers site. - For more information visit Important Advisory Regarding Recruitment Fraud | Tieto Blog Remote Type Remote Job Area Application and Product Development Business Unit Tech Consulting

Title: IT Data Engineer III Location US - Remote Remote/Hybrid Yes Position Level Individual Contributor III Employment Type Full time Career Field Information Technology Pay Type Annually Pay Range $ 117,000 - $ 124,000 Description & Requirements Culture Vision at Consumer Direct Care Network At CDCN, we strive to create a workplace where everyone is supported and motivated to be their best; we collaborate on shared goals and celebrate our accomplishments. WE WELCOME YOU INTO A GROWING COMPANY Consumer Direct Care Network is all about caring for people. Care is at our core, and we strive to live up to it every day. We provide services in 14 states across the USA, and our programs grow every year. We specialize in home and community-based services that support individuals with disabilities and older adults so they can remain in their homes and communities. JOB SUMMARY IT Data Engineer III is a senior-level position on the Enterprise Data team, responsible for leading the design, development, and support of complex enterprise data solutions across modern cloud platforms. This role plays a key leadership role in optimizing CDCN's data systems and processes for performance, scalability, and reliability while advancing our technical capabilities with cloud-native technologies. The IT Data Engineer III serves as a technical expert and mentor, guides ad hoc teams, and leads efforts to improve data workflows, architecture, and integration across the organization. This position requires deep technical expertise in Azure data platforms including Fabric and Synapse Analytics, strong collaboration skills, and the ability to communicate effectively with both technical and non-technical stakeholders. JOB DUTIES - Lead initiatives to design, develop, and maintain enterprise data warehouse systems and data integration pipelines used for analysis and reporting, leveraging Azure Fabric, Azure Synapse Analytics, and related Azure data platform technologies. - Design and implement scalable ETL/ELT (extract, transform, load) solutions across enterprise systems, leveraging advanced data engineering tools and technologies including Azure Data Factory, Databricks, and serverless data processing platforms. - Architect and optimize dimensional data models including fact tables, dimension tables, and slowly changing dimensions to support analytics and reporting requirements. - Lead response efforts to stakeholder data needs and system issues, serving as the primary technical contact for complex or escalated requests and ensuring alignment with business requirements and regulatory compliance. - Troubleshoot and resolve high-priority issues during regular business hours and as part of the after-hours on-call rotation, ensuring critical data systems remain operational and performing optimally. - Guide ad hoc teams in analyzing and improving data processes, system performance, and cost-efficiency through technical innovation, process redesign, and optimization of cloud infrastructure costs. - Provide technical mentorship and direction to peers and junior engineers across data projects and ongoing operations, fostering continuous learning and technical excellence. - Collaborate with engineers, analysts, and business partners to ensure that solutions align with strategic business goals, regulatory requirements, and industry best practices. - Implement and maintain data quality frameworks, validation rules, and monitoring mechanisms to ensure data accuracy, consistency, and reliability across enterprise systems. - Lead technical design reviews and code reviews, establishing and enforcing data engineering standards, best practices, and architectural principles. - Perform other duties as assigned, including leadership of special projects or enterprise-level initiatives. QUALIFICATIONS Education & Experience: - Bachelor's degree in Computer Science, Information Technology, Data Analytics, Data Science, Mathematics, or a related field required; equivalent professional experience will be considered. - 5–9 years of experience designing, developing, and supporting data platforms and enterprise data warehouse systems in production environments. - Proven ability to lead and serve as a technical expert on small to medium-sized projects and cross-functional initiatives. - Demonstrated experience mentoring junior engineers and contributing to team technical development. Core Technical Skills: - Expert-level experience with Azure Fabric including lakehouse architecture, notebooks, Delta Lake, data pipelines, and data warehouse design. - Deep hands-on experience with Azure Synapse Analytics including dedicated SQL pools, serverless SQL pools, Synapse pipelines, and performance optimization. - Expert-level SQL scripting with advanced proficiency in writing complex queries, stored procedures, query optimization, and performance tuning. - Deep experience in ETL/ELT development and data pipeline architecture across enterprise systems. - Advanced dimensional data modeling expertise including star schema, snowflake schema, fact tables, dimension tables, and slowly changing dimensions. - Expert-level experience with cloud data platforms such as Azure (primary), AWS, or Oracle Cloud. - Extensive hands-on experience with tools and technologies including Azure Data Factory, Azure Fabric, Azure Synapse Analytics, Databricks, Azure Data Lake Storage Gen2, Azure DevOps, SSMS, and Power BI. - Expert-level understanding of data structures and data exchange formats including ANSI X12, JSON, XML, and industry-standard data formats. - Proficiency in Python or PySpark for data processing and transformation tasks. DevOps & Engineering Practices: - Strong experience with version control systems (Git) and CI/CD practices for data engineering. - Familiarity with infrastructure as code (Terraform, ARM templates, or Bicep). - Experience implementing data quality frameworks and automated monitoring/alerting mechanisms. - Knowledge of data governance, security best practices, and regulatory compliance requirements. - Professional & Interpersonal Skills: - Demonstrated ability to communicate complex technical concepts clearly to both technical and non-technical audiences. - Strong problem-solving skills, attention to detail, and ability to manage multiple priorities under pressure. - Able to work independently or as a team lead, taking full ownership of technical solutions from design through implementation and support. - Proven ability to mentor peers and junior engineers, contributing to technical team development. - Ability to work effectively on-call and respond to critical production issues with urgency and professionalism. Machine Learning & AI (Preferred Qualifications): - Experience with Azure Machine Learning including model training, deployment, and inference pipelines integrated into data workflows - Familiarity with MLOps practices including model versioning, monitoring, retraining workflows, and model governance - Understanding of feature engineering and the role of data pipelines in preparing data for machine learning applications - Experience with Databricks ML features including MLflow and distributed model training - Knowledge of AutoML and automated feature selection tools within the Azure ecosystem - Experience implementing model monitoring and performance tracking in production environments - Familiarity with responsible AI principles including bias detection, explainability, and ethical AI considerations - Understanding of A/B testing frameworks and experimentation workflows in data-driven applications Other Requirements: - Must be able to successfully pass a background screening. - Willingness to maintain and expand technical certifications relevant to Azure data platforms. - Ability to work flexible and/or extended hours, if needed, to meet the job requirements. - Employees must provide their own reliable internet if working a remote/hybrid position The incumbent typically works in an office environment and uses a computer, telephone and other office equipment as needed to perform duties. The noise level in the work environment is typical of that of an office. Incumbent may encounter frequent interruptions throughout the workday. The employee is regularly required to sit, talk, or hear; frequently required to use repetitive hand motion, handle or feel, and to stand, walk, reach, bend or lift up to 20 pounds. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. WHAT'S IN IT FOR YOU When you join Consumer Direct Care Network, you will be exposed to numerous professional development opportunities. We welcome your contributions and value your integrity as we collaborate on work that moves us all toward a compassionate community. We have a long history of helping individuals build their careers in the home-care industry. This is truly a place where there is something for everyone, whether you are looking to support a particular lifestyle, seeking professional growth, or seeking new and challenging work, all in an expanding nationwide company with that small-company feel. Most importantly, you will experience the satisfaction of working in a culture built on caring. Caring for others comes naturally at Consumer Direct Care Network, based on our long history of connecting people and championing change, all geared toward helping others. We are proud of the longevity and loyalty of our employees. Their commitment to doing good work is what makes us a leader in the industry. As a Consumer Direct Care Network team member you will receive: - A rewarding career helping others - Fun and engaging work environment built on team unity - Job satisfaction knowing you make a difference in the work you do and lives we serve - Professional training to help advance your skills for career development Based on your position and employment status, you may be eligible for: - Medical, Dental, and Vision Insurance - Vacation accrued at 3.07 hours per pay period to use when accrued - Two Paid Floating Holidays - Nine Paid Federal Holidays - Paid Safe Sick Time accrued at 1 hour per 30 worked to use when accrued - Instant Earnings Option - 401(k) Retirement plan & discretionary company match - Company-Paid Life Insurance - Supplemental Life, Accident, Critical Illness, and Hospital benefits - Short and Long-Term Disability - Paid Parental Leave - Flexible Spending Account - Employee Assistance Program - Pet Insurance WHO WE ARE Consumer Direct Care Network specializes in home and community-based services that assist older adults and individuals of all ages with disabilities and impairments to continue to live their lives independently in their own homes and communities. We provide coordinated service delivery in 14 states. Our services span from financial management services and support brokerage to traditional agency in-home care and caregiving to behavioral health. We have extensive experience with Medicaid, Medicare, private insurance, and with supporting people who pay for their own care. Your opportunities within our network are endless, it’s not just a job, it’s a career… advance it with the Consumer Direct Care Network! The Consumer Direct Care Network and its subsidiaries are an Equal Opportunity Employer and drug-free workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. In accordance with the Immigration and Reform Control Act (IRCA), you may only work at Consumer Direct Care Network if you are legally authorized to work in the United States. Consumer Direct Care Network does not provide visa sponsorship or STEM OPT extensions to employees.

Role Description We are seeking an experienced Big Data Engineer to design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related big-data ecosystems. In this role you will be responsible for ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads. The ideal candidate will combine deep technical expertise across the Hadoop ecosystem with strong software engineering fundamentals and a clear understanding of how to deliver reliable, performant, and cost-effective data platforms in production environments. Key Responsibilities - Design, develop, and operate end-to-end big-data pipelines on Hadoop, ingesting data from a diverse mix of relational, file-based, streaming, and API-driven sources. - Build robust ETL/ELT workflows using Apache Spark, Hive, Pig, and Sqoop, with strong attention to data quality, idempotency, error handling, and recoverability. - Develop high-throughput streaming data pipelines using Kafka, Spark Streaming, or Flink, and integrate them with downstream analytical and operational systems. - Optimize Spark and MapReduce jobs through careful tuning of partitioning, memory, serialization, and skew handling to meet demanding SLAs at minimal cost. - Design and maintain data models and storage layouts on HDFS, Hive, HBase, and modern lakehouse formats (Parquet, ORC, Delta, Iceberg, Hudi) to balance flexibility and performance. - Implement data governance, lineage, and quality controls in collaboration with data governance and security teams. - Build robust monitoring, alerting, and logging strategies for big-data pipelines, including job-level SLAs and proactive failure detection. - Partner with data scientists and analysts to deliver curated, reliable, and well-documented datasets that accelerate their work. - Automate pipeline orchestration using Airflow, Oozie, or similar workflow engines, with clean dependency management and clear ownership boundaries. - Continuously evaluate and adopt new technologies in the big-data and cloud ecosystem (EMR, Databricks, Snowflake, BigQuery) where they offer meaningful improvements. - Lead performance reviews and architecture audits of existing pipelines, proposing concrete refactoring and optimization initiatives. - Document data architectures, schemas, pipeline behaviors, and operational runbooks in a way that makes the platform supportable as the team scales. - Mentor junior engineers and contribute to the team’s engineering standards and best practices. Qualifications - Bachelor’s degree in Computer Science, Engineering, or a related technical discipline. - Five or more years of professional experience designing and operating big-data pipelines on Hadoop. - Strong hands-on expertise with Apache Spark (Scala, Python, or Java) in production environments. - Solid experience with Hive, HDFS, Sqoop, HBase, and the broader Hadoop ecosystem. - Hands-on experience with streaming data platforms such as Kafka, Spark Streaming, or Flink. - Strong SQL skills and experience working with both relational and NoSQL data stores. - Experience with workflow orchestration tools such as Airflow or Oozie. - Solid understanding of distributed systems concepts, including partitioning, replication, and fault tolerance. - Strong scripting skills in Python or Shell. - Excellent troubleshooting, debugging, and documentation skills. Preferred Qualifications - Experience operating Hadoop on cloud platforms such as AWS EMR, Azure HDInsight, or Databricks. - Familiarity with modern lakehouse formats (Delta, Iceberg, Hudi). - Exposure to data governance tooling such as Apache Atlas or Collibra. - Experience with Kubernetes-based data platforms (Spark-on-K8s, Trino). - Hands-on experience with CI/CD and infrastructure-as-code in data engineering workflows. How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to [email protected] Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.

Role Description We are seeking a skilled Data Integration & Middleware Engineer to implement and manage scalable data pipelines and middleware solutions. The role will focus on orchestrating data workflows using Azure technologies such as Azure Data Factory (ADF), Azure Blob Storage, and Azure SQL Database, ensuring efficient ETL/ELT processing and high-quality data delivery. Qualifications - Strong experience with Azure Data Factory (ADF) for orchestration - Hands-on experience with ETL/ELT development - Experience with Azure Blob Storage / Data Lake - Proficiency in Azure SQL Database / SQL Server - Understanding of data warehousing concepts and data modeling - Knowledge of DevOps, CI/CD pipelines for data workflows - Experience with Azure Databricks or Synapse Analytics (Nice to Have) - Knowledge of data pipeline optimization and monitoring (Nice to Have) - Familiarity with API integrations and data connectors (Nice to Have) - Exposure to data governance and security practices (Nice to Have) - Azure certifications (e.g., AZ-900, DP-203) (Nice to Have) - Experience with real-time data processing frameworks (Event Hub, Service Bus) (Nice to Have) Requirements - Manage end-to-end data integration pipelines using Azure Data Factory (ADF) - Orchestrate and monitor data workflows, ensuring reliability, performance, and error handling - Implement/Manage ETL/ELT processes for data ingestion, transformation, and loading - Manage and optimize data storage solutions using Azure Blob Storage - Maintain structured data models in Azure SQL Database / Azure DB - Ensure data quality, validation, and governance across pipelines - Support integration with on-premise and cloud-based systems - Perform performance tuning and cost optimization across the data platform Benefits - Strong analytical and problem-solving abilities - Clear communication and stakeholder management skills - Ability to work in a collaborative, cross-functional environment - Attention to detail and commitment to data quality