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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - Healthcare Analytics Platform - **Company:** Guidehouse Inc. - **Location:** Washington, DC, United States (Remote available) - **Experience:** Expert - **Salary:** $77,000.0 - $129,000.0 - **Contract:** Permanent contract - **Skills:** Query Performance, Agile Methodology, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Health Informatics, Cloud Computing, Information Systems, Continuous Integration, Data Architecture, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Mart, Data Transformation, Data Migration, Data Systems, Data Visualization, Data Warehousing, Relational Databases, Distributed Data Store, Document-Oriented Databases, Revision Control Systems, Interoperability, Python (Programming Language), Operational Data Store, Power BI, Software Engineering, SQL Databases, Tableau (Software), Data Logging, Data Processing, Data Ingestion, Azure Data Factory, Fast Healthcare Interoperability Resources, Snowflake, Git, Data Lakes, Kubernetes, Information Technology, AWS Glue, Data Analytics, Health Level Seven International, Data Management, Tools for Reporting, Cloud Migration, Epic Caboodle, Software Version Control, Data Pipelines, Databricks, Microservices - **Published:** June 14, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=26cd21b6d066c311 ## About the Role Do you have experience in Version control systems?, Do you have a Bachelor's degree?, * US Citizenship or a Green Card is required * Bachelor's degree in Computer Science, Data Analytics, Software Engineering, Information Systems, or related fields * A minimum of FIVE (5) years of experience in data engineering, ETL/ELT development, or data platform engineering in a healthcare setting * Experience working with healthcare data, including claims, clinical, payer, or population health datasets * Experience working with healthcare data interoperability standards (e.g., FHIR, HL7) * Proficiency in Python and SQL for data engineering and transformation workloads * Hands-on experience designing and building ETL/ELT pipelines and data ingestion frameworks * Experience working with modern cloud data platforms or ETL/ELT tools (e.g., Databricks, Azure Data Factory, AWS Glue) * Experience working with lakehouse or medallion-style architectures for analytics platforms * Strong knowledge of relational database design, data warehouses, and/or data lakes (e.g., star/snowflake schemas) * Experience working with relational and/or distributed data systems, including data modeling * Experience working in a cloud environment (AWS or Azure) supporting data solutions * Experience with CI/CD practices and version control tools (e.g., Git) * Experience using monitoring and logging tools to support data pipeline reliability * Experience working with PHI and healthcare data privacy/security requirements * Ability to work effectively in an Agile development environment * Strong analytical and troubleshooting skills, and the ability to communicate technical concepts clearly to clients, engineers, and business stakeholders * Ability to work independently in a fast-paced, client-facing environment What Would Be Nice To Have: * Previous experience working with Epic and/or Athena in a healthcare setting for data engineering * Previous experience with Exasol or similar analytics platform * AWS, Azure, Databricks, Snowflake or other data engineering-related certifications * Experience with data visualization or analytics tools (e.g., Tableau, Power BI) * Exposure to microservices-based architectures or AI/ML-enabled data pipelines * Prior consulting experience ## Description We are seeking a Data Engineer to support the design and development of an enterprise Contract Performance Analytics platform for a large healthcare system. This role will focus on data architecture, ELT/ETL pipeline development, and integration of clinical, claims, and operational data into a scalable analytics ecosystem. The Data Engineer will play a key role in building a unified data system that enables insights across value-based care contracts (MSSP, Medicare Advantage, Commercial, and Employer Health Plans). This platform integrates EHR cloud-based data processing and an enterprise data warehouse to support analytics and reporting. * Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load healthcare data from diverse structured and unstructured sources * Develop pipelines to process data from CMS and payer files (CCLF, paid claims, PUG) as well as Epic (Caboodle, Clarity) data models and extracts * Build and optimize data models to support analytics, reporting, and operational use cases, including BI and downstream analytics consumption * Transform raw data into standardized, analytics-ready canonical data models and curated data marts * Build lakehouse/medallion architecture, data ingestion patterns, and orchestration frameworks * Implement and maintain CI/CD pipelines for data engineering workflows, including pipelines and scheduled jobs, using version control and automation tools * Collaborate with database administrators, analysts, and application teams to integrate data sources, design schemas, and support downstream data consumers * Ensure data quality, integrity, and accuracy through validation, monitoring, logging, and alerting * Support data migration, integration, and modernization initiatives, including legacy system upgrades, optimization of large-scale ETL pipelines, query performance, and cloud adoption efforts * Troubleshoot and resolve issues in development and production environments to maintain stable and reliable data pipelines * Document data flows, pipelines, test cases, and technical solutions to support knowledge sharing and compliance requirements * Stay current with emerging tools, technologies, and best practices in data engineering and cloud platforms ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Tips, Techniques, and Common Pitfalls Debugging Kafka](https://www.wearedevelopers.com/videos/838-tips-techniques-and-common-pitfalls-debugging-kafka) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)