Data Engineer, Synthetic Data Generation

Humana•Louisville, KY

8d•Remote

About The Position

The Data Engineer (Software Engineer 2) at Humana is responsible for designing, generating, and validating high-quality artificial member data to support testing, analytics, and system integration. You will build synthetic data scenarios using tools such as GenRocket, ensuring alignment with complex healthcare business rules, membership processes, and data models. The Data Engineer 2 oversees the end-to-end data lifecycle—from EDI intake through transformation, validation, and integration into downstream platforms—ensuring data integrity, accuracy, and usability. You will collaborate with business and technical partners to deliver reliable, compliant, and test-ready data assets, while identifying opportunities to improve data generation, validation, and integration processes. You will operate within Humana's enterprise data governance, security, and architectural standards. You will report to an Associate Director of Technology Leadership. This role may require occasional travel into one of our hub locations; Tower Hall Park office, Dallas TX or Waterside Building, Louisville KY. Candidates residing near or within 50 miles of one of the hub locations are preferred. The Data Engineer (Software Engineer 2) collaborates with teams to design, build, and maintain scalable data solutions. You will have a specialized focus on synthetic member data generation, EDI processing, and data validation. The goal of these efforts is to support Humana's business strategies. You will ensure data is accurate, testable, and aligned with enterprise standards for reliability, accessibility, and security.

Requirements

Bachelor's degree in Computer Science, Information Systems, or related field.
3+ years experience with SQL, relational databases, and data modeling.
Experience working with EDI/X12 healthcare transactions (834, 837 preferred).
Travel up to 10% into one of our hub offices as business requires.

Nice To Haves

Experience in healthcare domains, membership, enrollment, claims, dental, or vision data.
1 or more years of experience with synthetic data generation tools (e.g., GenRocket) or similar frameworks.
Hands-on experience with data integration and ETL tools (e.g., Informatica, Spark, and Python).
Knowledge of data warehousing and cloud platforms.
Experience with test data management (TDM) practices.
Understanding of data governance and security standards.

Responsibilities

Manage, parse, validate, and reconcile ANSI X12 transactions, including: 834 (Enrollment), 837 (Claims), and additional formats supporting dental and vision lines of business.
Ensure accurate ingestion and transformation of EDI data into internal systems.
Design and execute test scenarios to generate synthetic member data using GenRocket, aligning with healthcare business rules and domain requirements.
Leverage knowledge of membership data, enrollment processes, and downstream impacts to ensure artificial data is realistic and fit for purpose.
Oversee end-to-end synthetic data lifecycle, from initial design through deployment and validation.
Validate artificial data for completeness, integrity, and alignment with data models and business rules.
Identify and resolve data anomalies prior to system integration.
Ensure generated data meets testing, regulatory, and operational requirements.
Load generated and transformed data into enterprise platforms and data warehouses.
Monitor ingestion processes and verify successful processing across systems.
Develop and maintain data pipelines supporting integration, transformation, and delivery of datasets.
Use SQL to query, analyze, and manipulate data for validation, testing, troubleshooting, and reporting.
Investigate data discrepancies and perform root cause analysis using SQL and supporting tools.
Partner with business stakeholders, QA teams, architects, and engineers to ensure data aligns with test case requirements and system needs.
Translate business requirements into technical data solutions.