Data Engineer – Healthcare Analytics Platform

Guidehouse is seeking a Data Engineer to design and develop an enterprise Contract Performance Analytics platform for a large healthcare system. The role focuses on data architecture, ELT/ETL pipelines, and the integration of clinical, claims, and operational data for analytics. This onsite opportunity in Washington, DC offers a salary range of USD 77,000 to 129,000 per year and a comprehensive benefits package.

Benefits

• Medical, Rx, Dental & Vision Insurance
• Personal and Family Sick Time & Company Paid Holidays
• Position may be eligible for a discretionary variable incentive bonus
• Parental Leave and Adoption Assistance
• 401(k) Retirement Plan
• Basic Life & Supplemental Life
• Health Savings Account, Dental/Vision & Dependent Care Flexible Spending Accounts
• Short-Term & Long-Term Disability
• Student Loan PayDown
• Tutition Reimbursement, Personal Development & Learning Opportunities
• Skills Development & Certifications
• Employee Referral Program
• Corporate Sponsored Events & Community Outreach
• Emergency Back-Up Childcare Program
• Mobility Stipend

Responsibilities

• Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load healthcare data from diverse structured and unstructured sources
• Build pipelines to process data from CMS and payer files (CCLF, paid claims, PUG) as well as Epic Caboodle and Clarity data models and extracts
• Create and optimize analytics-ready data models to support analytics, reporting, and downstream BI consumption
• Transform raw data into standardized canonical data models and curated data marts
• Develop lakehouse or medallion architectures, data ingestion patterns, and orchestration frameworks
• Implement and maintain CI/CD pipelines for data workflows, including scheduled jobs, using version control and automation tools
• Collaborate with DBAs, analysts, and application teams to integrate data sources, design schemas, and support downstream consumers
• Ensure data quality, integrity, and accuracy through validation, monitoring, logging, and alerting
• Support data migration, integration, and modernization initiatives, including legacy upgrades, large-scale ETL optimization, query performance, and cloud adoption
• Troubleshoot and resolve issues in development and production environments to maintain reliable data pipelines
• Document data flows, pipelines, test cases, and technical solutions to support knowledge sharing and compliance
• Stay current with emerging tools, technologies, and best practices in data engineering and cloud platforms

Requirements

• US Citizenship or a Green Card is required
• Bachelor’s degree in Computer Science, Data Analytics, Software Engineering, Information Systems, or related fields
• Minimum of five (5) years of experience in data engineering, ETL/ELT development, or data platform engineering in a healthcare setting
• Experience with healthcare data, including claims, clinical, payer, or population health datasets
• Experience with healthcare interoperability standards such as FHIR and 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 with modern cloud data platforms or ETL/ELT tools (Databricks, Azure Data Factory, AWS Glue)
• Experience with lakehouse or medallion architectures for analytics platforms
• Strong knowledge of relational database design, data warehouses, and/or data lakes with star/snowflake schemas
• Experience with relational and distributed data systems, including data modeling
• Experience in a cloud environment (AWS or Azure) supporting data solutions
• Experience with CI/CD practices and version control tools (Git)
• Experience using monitoring and logging tools to support data pipeline reliability
• Experience 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

Technologies

• Python
• SQL
• Databricks
• Azure Data Factory
• AWS Glue
• Git
• Tableau
• Power BI
• AWS
• Azure

Nice to have

• Previous experience with Epic and/or Athena in a data engineering role
• Experience with Exasol or similar analytics platforms
• Certifications in AWS, Azure, Databricks, Snowflake, or related data engineering tools
• Experience with data visualization or analytics tools (Tableau, Power BI)
• Exposure to microservices architectures or AI/ML enabled data pipelines
• Prior consulting experience