Data Engineer
About The Position
Enlace Health delivers the only end-to-end solution that solves the infrastructure challenges driving today’s unsustainable healthcare system. Connecting payers, providers, and patients, Enlace™ empowers any type of healthcare delivery model, from facilitating retrospective programs to enabling risk for prospective programs. Combining executive-level healthcare DNA with an extensible technology platform, Enlace is the bridge from chaotic healthcare to the healthcare world when Triple Aim optimization is truly realized. At Enlace Health, our people are our greatest asset. Our culture is founded upon integrity, hard work, and the relentless pursuit to make a difference. We think creatively, we like a challenge and draw inspiration from each other. As the Data Engineer, you will be responsible for building and operating the data ingress and normalization layers of a multi-tenant healthcare lakehouse. This role will design and deliver scalable data pipelines and healthcare datasets that power analytics and product capabilities, enabling interoperability and value-based care insights across payer and provider ecosystems. The Data Engineering team owns the Bronze (raw ingestion) and Silver (normalized canonical) layers of our Medallion architecture, with a strong focus on healthcare claims data and data quality. Success Metrics In 3 Months: Become proficient in Enlace’s data platform architecture, SDLC, and deployment processes. Deliver initial ingestion and normalization contributions to Bronze and Silver layers. Demonstrate operational fluency: monitoring signals, triage basics, and reliable delivery habits. In 6 Months: Independently own ingestion and normalization pipelines with reliable operations. Implement canonical mappings for new datasets and contribute to testing and DQ automation. Participate effectively in production support, improving runbooks/alerts/backfills. In 12 Months: Deliver demonstrably high-quality canonical datasets with strong operational maturity. Improve pipeline reliability and maintainability through iterative hardening and automation.
Requirements
- Professional experience working with healthcare claims data (commercial and CMS).
- Experience building production ETL/ELT pipelines and data ingress processes.
- Strong Python development skills for data engineering.
- Advanced SQL expertise including performance optimization and tuning.
- Hands-on experience with Spark-based data processing.
- Experience working in AWS-native or equivalent cloud data ecosystems.
- Experience designing and implementing data models.
- Familiarity with data lake and lakehouse architectures and operating production pipelines.
- Located in Atlanta, GA and comfortable with a hybrid work environment.
- Participation in a flexible on-call rotation supporting data platform operations.
Nice To Haves
- Familiarity with open table formats (e.g., Apache Iceberg); required depth at Senior level.
- Experience building multi-tenant data platforms and supporting tenant isolation.
- Knowledge of healthcare interoperability and canonical modeling.
- Experience with Infrastructure as Code (Terraform, AWS CDK).
- Experience implementing CI/CD pipelines (GitHub Actions, AWS CodePipeline).
- Familiarity with orchestration frameworks such as AWS Step Functions.
- Familiarity with cloud monitoring/observability patterns; CloudWatch preferred.
Responsibilities
- Lakehouse/Data Mesh Development
- Design and operate ingestion and normalization pipelines across the Bronze and Silver layers of a multi-tenant healthcare lakehouse.
- Develop secure batch and streaming ingestion processes supporting schema drift, replay, and PHI-compliant storage.
- Standardize commercial and CMS claims data into canonical healthcare data models spanning claims, eligibility, members, and providers.
- Design and maintain referential integrity, de-duplication, and temporal modeling frameworks enabling longitudinal analytics.
- Build scalable Spark-based transformation pipelines and reusable ingestion frameworks aligned to data mesh principles.
- Optimize storage, partitioning, and schema evolution strategies using open table formats.
- Implement automated data quality, reconciliation, and monitoring to ensure reliable production SLAs.
- Deploy and manage platform infrastructure, CI/CD workflows, and observability using Infrastructure as Code and cloud-native tooling.
- Utilize cloud-native monitoring tooling; CloudWatch familiarity is a plus.
- Data Platform Delivery & Client Integration
- Design, build, and operate scalable ingestion and normalization pipelines for healthcare datasets.
- Support technical onboarding of new client integrations, validating inbound data feeds and ensuring reliable operationalization.
- Implement and optimize canonical healthcare data models, Spark transformations, and data quality/reconciliation frameworks.
- Architecture, Collaboration & Platform Evolution
- Partner cross-functionally to translate product and analytics requirements into pragmatic, scalable technical designs.
- Architect reusable ingestion and transformation frameworks that improve scalability, performance, and operational reliability.
- Lead complex onboarding efforts and drive continuous platform optimization across domains.
Benefits
- FREE medical, dental, and vision insurance for employees on select plans
- $1740 annual contribution into qualifying HSAs
- UNLIMITED time off
- Matching 401(k) plan
- Mac laptop and accessories
- Company-paid short-term and long-term disability
- Company-paid life insurance
- Employee Assistance Program
- Annual professional development stipend
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
