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Closed on July 16, 2026.
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Data Engineer – Healthcare Analytics Platform
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Job Description
Guidehouse is seeking a Data Engineer to design and build an enterprise Contract Performance Analytics platform for a large healthcare system. This onsite role in Atlanta, GA offers a salary range of USD 77,000 to 129,000 per year, along with a comprehensive benefits package. You will influence data architecture, craft robust ELT/ETL pipelines, and integrate clinical, claims, and operational data into a scalable analytics ecosystem.
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
- Tuition 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 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) and Epic data models and extracts (Caboodle, Clarity)
- Create and optimize data models to support analytics, reporting, and operational use cases, including BI consumption
- Transform raw data into standardized, analytics-ready canonical data models and curated data marts
- Construct lakehouse and medallion style architectures, data ingestion patterns, and orchestration frameworks
- Implement and maintain CI/CD pipelines for data workflows, with version control and scheduled jobs
- Collaborate with DBAs, 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 upgrades, large-scale ETL optimization, query performance, and cloud adoption
- Troubleshoot and resolve issues in development and production environments to maintain stable 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
Technologies
- Python
- SQL
- Databricks
- Azure Data Factory
- AWS Glue
- Git
- Tableau
- Power BI
- AWS
- Azure
- Snowflake
- Exasol
- Epic
- Caboodle
- Clarity
- Athena
Requirements
- 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 with healthcare data interoperability standards (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 with modern cloud data platforms or ETL/ELT tools (Databricks, Azure Data Factory, AWS Glue)
- Experience with lakehouse or medallion-style architectures
- Strong knowledge of relational database design, data warehouses, and/or data lakes (star/snowflake schemas)
- Experience 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 (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, with the ability to communicate technical concepts clearly to clients, engineers, and business stakeholders
- Ability to work independently in a fast-paced, client-facing environment
Nice to have
- Previous experience working with Epic and/or Athena in a healthcare data engineering role
- Experience with Exasol or a similar analytics platform
- Certifications in AWS, Azure, Databricks, Snowflake, or related data engineering tools
- Experience with data visualization or analytics tools (Tableau, Power BI)
- Exposure to microservices based architectures or AI/ML enabled data pipelines
- Prior consulting experience