This page tracks remote data engineer openings that are location-eligible for Ohio.
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Role Description ExeQut is hiring a Senior Data Engineer (Microsoft Fabric & Power BI) to build a new data warehouse end to end. The platform is Microsoft Fabric. The pattern is medallion (Bronze, Silver, Gold) with a Kimball-style dimensional model on top. A normal week looks like this: - Build pipelines from AS/400 (using Qlik Replicate or JT400) and from Azure Database for PostgreSQL (via Fabric Mirroring) into Bronze - Write transformations from Bronze into Silver. Clean, deduplicate, conform - Model the Gold layer. Star schemas, conformed dimensions, slowly changing dimensions where history matters - Build certified Power BI semantic models in Direct Lake mode. Write DAX measures. Set up row-level security - Reconcile the new outputs against legacy reports during parallel run - Eventually, help wire up Power BI Copilot and a first custom AI agent on the same semantic layer Qualifications - At least one year of real production work in Microsoft Fabric - Strong Power BI. Semantic models, DAX, row-level security - Kimball dimensional modeling. Star schemas, conformed dimensions, the SCD types and when to use each - Advanced SQL - Python or PySpark for the transformation work - Comfortable in Azure as the underlying platform - CI/CD for data work. Fabric Deployment Pipelines, Azure DevOps, or GitLab Requirements - Any AS/400 or DB2 for i background - Hands-on with Power BI Copilot, Azure AI Foundry, or any agent development - Microsoft Purview for governance and lineage Benefits - Fluent English communication (written and verbal) - Availability during US East Coast core hours (9 AM - 1 PM EST) from Monday to Friday Role Type - Full-Time Location - Remote (aligned with USA time zones) Working Days - Monday - Friday Hiring Timeline - Immediate
Located in Atlanta, Georgia, Emory University is one of the world’s leading research universities. A top-ranked, private institution dedicated to serving huma
Role Description Winship is seeking qualified candidates for the Oncology Data Specialist-Certified position. Position details are as follows: - Responsible for case finding, data abstraction and follow-up of patients with a diagnosis of cancer. - Performs clinical data abstraction by capturing the complete patient history, diagnosis, staging and treatment information for all patients accessioned into the cancer registry in accordance with the guidelines established by the American College of Surgeon Commission on Cancer and the Georgia Central State Cancer Registry. - Utilizes cancer data collection principles and assigns codes to the extracted data based on established coding systems (STORE, SEER, ICD-O3, AJCC Staging 8th Ed) to ensure consistency and compliance with reporting guidelines. - Performs quality assurance activities when assigned such as: - Review of abstracted data for accuracy - Peer reviews - Resolution of data edits - Conduct non-reportable audits to ensure that all reportable cases are captured - Consolidation of multiple data reports into a concise record for each cancer case - Inclusion of additional treatment and follow-up information obtained after completion of the initial abstract - Attends and participates in professional conferences, seminars, or workshops to keep current on information related to the Cancer Registry and cancer treatment. - Adheres to HIPAA privacy regulations and other virtual office procedures. - Performs other duties as assigned. Qualifications - Associate's degree in a related field. - Must be an (ODS-C) Oncology Data Specialist Certified by the National Cancer Registrar Association. - **Please only apply if you are ODS-C Certified** Company Description About Winship Cancer Institute of Emory University: - Dedicated to discovering cures for cancer and inspiring hope. - Georgia’s only National Cancer Institute-designated Comprehensive Cancer Center. - Researching, developing, teaching, and providing novel and highly effective ways to prevent, detect, diagnose, treat, and survive cancer. - Leading cancer specialists collaborating across disciplines to tailor treatment plans to each patient’s needs and type of cancer. - Innovative therapies and clinical trials. - Comprehensive patient and family support services. - A personalized care experience aimed at easing the burden of cancer. - Winship is Where Science Becomes Hope®.
Role Description We are seeking two highly skilled Senior Data Engineers to join a fast-paced, data platform delivery team supporting a UK-based client. The successful candidates will play a key role in designing, building, and maintaining scalable data solutions on Microsoft Azure, specifically leveraging Azure Synapse and related services. This role requires experienced professionals who can operate independently, engage effectively with stakeholders, and deliver high-quality data engineering solutions in a distributed, remote environment. - Design and develop scalable data pipelines and data processing solutions on Azure - Build and optimize solutions using Azure Synapse Analytics - Integrate data from multiple sources into cloud-based data platforms - Ensure high-quality, reliable, and efficient data ingestion and transformation pipelines - Collaborate with stakeholders to understand requirements and translate them into technical solutions - Support and enhance existing data platforms and architectures - Troubleshoot and resolve data and platform-related issues - Deliver solutions aligned with best practices in data engineering and cloud architecture - Work independently while managing deliverables across the project lifecycle Qualifications - Strong hands-on experience with Microsoft Azure Data Services - Azure Synapse Analytics - Proven experience in Data Engineering (data pipelines, ETL/ELT processes) - Experience working with data integration and transformation tools - Data warehousing concepts and architectures - Exposure to cloud-based data platforms and modern data ecosystems Requirements - Ability to work independently and drive delivery without close supervision - Strong problem-solving and analytical thinking - Experience working in remote/distributed teams - Understanding of basic Business Intelligence concepts and workflows - Excellent communication skills (verbal and written English) - Ability to engage confidently with international (UK-based) stakeholders - Strong collaboration and stakeholder management skills - Self-motivated and delivery-focused mindset Benefits - Experience with additional Azure services (Data Factory, Databricks, etc.) - Exposure to large-scale or enterprise data platform projects - Experience supporting UK or international clients
Conserving the lands and waters on which all life depends.
• The Senior Data Engineer focuses on the development of analytics-oriented data models and data ingestion pipelines related to three core data domains: Conservation Effectiveness, Finance, and Human Resources. • They analyze and document end user and technology-user business requirements for data projects with wide range of complexity at varying levels of impact on organization-wide initiatives. • They design and develop new, complex technology systems and solutions according to system requirements following TNC methodology and development best practices. • Create data pipelines to ingest data from Workday and the conservation Hub into a shared data lake for future analysis. • Utilize fact/dimension design principles to design, build, and maintain datamarts across three core data domains: Conservation Effectiveness, Finance, and Human Resources. • Work with Data Governance to ensure data in the above domains are properly registered in master data management systems and data catalogs, where applicable.
Atlassian is a publicly-traded computer software business specializing in collaboration, development, and issue-tracking software for teams. As an employer, Atlassian maintains a t
Role Description Atlassian is looking for an Engineering Leader to join the Data Engineering team and build data products that power product strategy and important decisions across the organization. We are looking for a leader passionate about building systems at scale. You will lead a world-class data engineering practice, shape up technical strategy and data architecture, and develop data products to enable reporting, analytics, data science, machine learning, and AI workloads. - Lead a high-performing organization focused on designing, building, and scaling foundational analytical data products. - Partner closely with cross-functional stakeholders to define data strategies, improve data quality and reliability. - Deliver reusable data models, pipelines, and platforms that enable analytics at scale. - This is a critical leadership role at the intersection of data architecture, engineering excellence, and business impact. Qualifications - 15+ years of experience in building and scaling data teams with a focus on data strategy, infrastructure planning, architecture, and data products. - 10+ years of experience leading data engineering teams, managing managers of managers, and scaling organizations with over 20+ engineers across geographies. - 10+ years of experience delivering data and analytics solutions for product teams. - Product sense with an understanding of product drivers and how to guide value using data across the organization. - Demonstrated experience developing influential relationships and trust with senior leaders across different departments. - Prior experience partnering with Analytics, Data Science, Engineering, and Product Management teams. - Experience building Microservices and RESTful APIs. - Experience implementing DevOps best practices within the data platform, including solutions for CI/CD, data observability, monitoring, and lineage. - Experience with BI tools like Tableau, Amplitude, and Redash. - A graduate degree in Computer Science or a similar subject area. Requirements - Experience working for SAAS companies (preferred but not required). - Experience with Machine Learning (preferred but not required). - Committed code to open source projects (preferred but not required). Benefits - Wide range of perks and benefits designed to support you and your family. - Health and wellbeing resources. - Paid volunteer days. - Additional offerings to engage with your local community. Compensation At Atlassian, we strive to design equitable, explainable, and competitive compensation programs. The baseline of our range is higher than that of the typical market range, but we expect to hire most candidates near this baseline. Base pay within the range is ultimately determined by a candidate's skills, expertise, or experience. - Zone A: $234,000 - $305,500 - Zone B: $210,600 - $274,950 - Zone C: $194,400 - $253,800 This role may also be eligible for benefits, bonuses, commissions, and equity. Please visit go.atlassian.com/payzones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. Company Description At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. - We believe that the unique contributions of all Atlassians create our success. - We never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. - All your information will be kept confidential according to EEO guidelines. - To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. To learn more about our culture and hiring process, visit go.atlassian.com/crh.
Role Description Lead client SMEs through complex schema mapping and source-to-target validation, including automated reconciliation scripts across sandboxes and production cutovers. - Expert in Automation Bypass strategies and Identity Resolution rules to prevent duplicate records and performance degradation during high-volume loads. - Architect Zero Copy Federation via Salesforce Data Cloud (Data 360), mapping Databricks DLOs to Salesforce DMOs for 10–25 year historical datasets. - Lead "Receiving Pipes" development using Bulk API 2.0 and scripting (Python, Node, or SFDX) to ingest 10 years of active and historical records. - Perform complex object mapping from flat legacy tables into normalized Salesforce objects (Accounts, Cases, custom Disaster objects). - Define a hybrid schema bridging physically migrated (10-year) and Zero Copy historical (10–25 year) data. - Configure Match and Reconsolidation rules to link survivor records across 15+ years of Databricks history to active Salesforce cases. - Build Parent-to-Child load sequencing (e.g., Disaster before Case). - Manage Bulk API 2.0 concurrency limits and batch failures to ensure efficient, reliable dry runs and cutovers. Qualifications - Technical expertise in schema mapping and validation. - Experience with Salesforce Data Cloud and Databricks. - Proficiency in scripting languages such as Python, Node, or SFDX. - Strong understanding of data migration and object mapping. Requirements - Experience with Bulk API 2.0 and data ingestion processes. - Ability to configure Match and Reconsolidation rules. - Knowledge of managing data concurrency and batch processing. Benefits - Competitive salary. - Health and wellness programs. - Opportunities for professional development.
• Design & Build: Architect and maintain the company’s core data infrastructure, including pipelines, warehousing, ingestion, transformation, and orchestration systems. • Own the Data Platform: Take end-to-end responsibility for the scalability, reliability, and security of the data platform ensuring high-quality data is accessible across the organization. • Set the Standard: Establish and own data engineering best practices, including data modeling, pipeline design, and observability patterns that the broader team can build on. • Champion Data Quality: Drive data quality and observability initiatives across the platform, ensuring stakeholders can trust the data they rely on. • Collaborate Cross-Functionally: Partner closely with engineering, product, and analytics teams to understand data needs and translate them into concrete technical solutions. • Lead & Mentor: Mentor engineers on data engineering principles and patterns, and contribute actively to hiring and team development.
• Design, build, and maintain ELT/ETL pipelines that move data reliably from source systems into a cloud data warehouse environment. • Write clean, performant, and well-documented SQL to transform raw data into analyst-ready models and reporting layers. • Develop and maintain Power BI dashboards and reports that give business stakeholders clear, trusted views of company performance. • Apply best practices in data modeling within Power BI (star schemas, DAX measures, performance optimization). • Actively use AI tools (such as LLM assistants, copilots, and agentic workflows) to accelerate development and improve code quality. • Engage directly with business stakeholders to understand data needs in context.
• Inherit, evaluate, and take full ownership of existing ETL/ELT pipelines — identifying what to preserve, improve, or replace based on performance, reliability, and long-term maintainability. • Design and build scalable pipeline improvements or net-new solutions where current practices fall short. • Monitor pipeline health, troubleshoot data quality issues, and proactively resolve performance and reliability problems. • Manage and evolve orchestration tooling with openness to adopting better alternatives as infrastructure needs grow. • Optimize query performance, pipeline efficiency, and resource utilization across Convo’s data environment. • Participate in testing, deployment, and monitoring practices that promote long-term reliability and scalability. • Develop and maintain scalable data transformation processes, schema design, and data models that support evolving business requirements. • Establish and evolve data quality testing frameworks - building practices that catch issues early and create lasting internal trust in our data. • Own data governance, documentation, lineage, version control, and data quality standards across the organization. • Serve as the primary internal resource for data engineering guidance and recommendations, helping set standards and informing data infrastructure decisions across the organization. • Work closely with the data analyst to translate business questions into reliable, queryable data structures. • Educate and guide non-technical stakeholders on how to work effectively with data, what is and isn’t feasible, and how to frame data requests clearly. • Explore and implement tooling to enable self-service data discovery for internal teams, reducing bottlenecks and empowering stakeholders to answer their own questions. • Collaborate with Product, Engineering, Finance, Operations, and Data Science stakeholders to support reporting, forecasting, and business intelligence needs. • Partner with Product and Engineering teams to integrate analytics, event tracking, and reporting into products and platforms. • Establish and document data engineering standards, workflows, and best practices at Convo — building a foundation that is sustainable, well-understood, and not dependent on any single person. • Contribute to improvements in data architecture, tooling, monitoring, automation, and engineering best practices. • Evaluate emerging technologies and tooling to improve efficiency, automation, and accessibility of data systems. • Maintain clear technical documentation and operational standards that support long-term maintainability. • Exercise sound technical judgment in balancing immediate business needs with long-term platform sustainability. • Maintain strong confidentiality and discretion when handling sensitive organizational, financial, operational, and employee data.
Role Description The Manager, Data Engineering role is accountable for the operational excellence, stability, and evolution of the enterprise data platform supporting CenterWell Pharmacy (CWP) and Pharmacy Benefits Management (PBM). This role partners closely with engineering leads and cross-functional stakeholders to prioritize work, ensure platform reliability, and drive continuous improvement of data platform capabilities. Unlike traditional management roles, this position is a hands-on operational leader responsible for executing critical platform accountabilities while also leading and developing a high-performing team. This role focuses on enabling engineering teams to concentrate on software development and innovation by owning operational governance, platform health, financials, and delivery oversight. The Manager, Data Engineering, works within defined enterprise guidelines and processes, applying advanced technical and operational knowledge to solve moderately complex problems. The role receives objectives and determines appropriate approaches, resources, priorities, and execution plans while ensuring alignment with enterprise strategy. This role leads a blended team consisting of approximately 25 to 40 contractors and 3 to 6 associates, with team size fluctuating based on business demand and project needs. Key Responsibilities - Oversee all aspects of data platform operations, including: - SDLC adherence - Change management - Financial governance - Vendor coordination - Cloud cost optimization - Technology lifecycle activities - Collaborate across: - Engineering - Product - Security - Compliance - Business teams Success Profile - Balance of: - Technical depth - Operational rigor - Financial ownership - People leadership - Ability to operate effectively in a fast-paced, highly regulated healthcare environment. Qualifications - Bachelor’s degree in computer science, Information Technology, Engineering, or related field; or equivalent experience - 8+ years of experience in data engineering, software engineering, or enterprise data platform environments - 2+ years of experience leading or managing technical teams, including direct or matrixed reports - Hands-on experience operating and supporting cloud-based data platforms (e.g., Snowflake, Databricks, Azure, or similar technologies) - Strong knowledge of Software Development Life Cycle (SDLC), DevOps practices, and operational readiness disciplines - Experience managing application lifecycle activities, including deployments, documentation, technical debt, and production support - Demonstrated experience managing change control processes using enterprise tools (e.g., ServiceNow or similar systems) - Experience with financial accountability, including budgeting, forecasting, and cloud cost management - Proven ability to manage multiple priorities, projects, and operational demands in a fast-paced environment - Experience working in cross-functional environments, partnering with business and technology stakeholders to align priorities and delivery - Strong communication, leadership, and stakeholder management skills with ability to influence across organizational levels - Demonstrated ability to drive operational excellence, improve system stability, and implement quality improvement practices (e.g., shift-left defect identification) - Experience supporting compliance, security, and risk management practices (e.g., vulnerability management, cyber hygiene, or similar disciplines) Preferred Qualifications - Experience supporting healthcare, pharmacy, or Pharmacy Benefits Management (PBM) domains - Experience operating enterprise data platforms supporting high-volume, near real-time ingestion and analytics workloads - Familiarity with tools and processes such as ServiceNow (SNOW), EAPM, and Technology Lifecycle Management (TLM) - Experience managing vendor relationships, contracting processes, and Statements of Work (SOWs) - Exposure to data governance, data quality, and regulatory requirements (e.g., HIPAA, PCI, or DSCSA) - Experience with cloud cost optimization strategies and FinOps practices - Experience leading or supporting large-scale platform modernization or transformation initiatives - Strong understanding of data engineering frameworks, including ETL/ELT pipelines, data lakes, and data warehouses - Experience implementing monitoring, observability, and production support processes for data platforms - Master’s degree in computer science, Information Technology, Business Administration, or related field - Agile, Scrum, or DevOps certifications Travel While this is a remote position, occasional travel to Humana's offices for training or meetings may be required. Scheduled Weekly Hours 40 Pay Range The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc. $129,300 - $177,800 per year This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance. Benefits - Medical, dental and vision benefits - 401(k) retirement savings plan - Time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave) - Short-term and long-term disability - Life insurance - Many other opportunities Equal Opportunity Employer It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements.
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SQL, Python, ETL, Azure, Data Engineering, Databricks
