Data Engineer – Healthcare Analytics Platform

Guidehouse•Atlanta, GA

11h•Hybrid

About The Position

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.

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 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

Nice To Haves

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

Responsibilities

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

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