Note: The job is a remote job and is open to candidates in USA. Astrana Health is seeking a Lead Data Engineer to design, build, and operate components of its enterprise data platform. The role develops healthcare data pipelines, models, APIs, and applications while ensuring platform reliability, performance, security, and engineering standards.
Responsibilities
- Lead the design, development, and delivery of core platform components, including the Constellation Lakehouse in Databricks, Connect API (GraphQL) layer, and Lakebase-backed applications
- Build and maintain scalable batch and incremental data pipelines using Databricks, Apache Spark, PySpark, SQL, and Delta Lake
- Integrate data from transactional databases, APIs, files, and external partners into governed datasets that support analytics and operational applications
- Design and maintain unified healthcare data models spanning membership, providers, claims, encounters, clinical data, and other business domains
- Develop reliable ingestion and transformation processes, including change data capture, schema evolution, deduplication, historical tracking, and reconciliation
- Build and optimize data access layers and APIs in partnership with software engineering teams, supporting consistent business definitions and reliable downstream consumption
- Develop and support Lakebase-backed applications and PostgreSQL data structures, including integration with lakehouse datasets and application services
- Maintain and optimize Databricks workspaces, compute resources, job orchestration, and environment configurations in collaboration with infrastructure and security teams
- Implement data governance and access controls through Unity Catalog and established organizational standards, including permissions, lineage, and auditability
- Establish automated data quality checks, source-to-target reconciliation, freshness monitoring, and alerting to ensure datasets are accurate, complete, and usable
- Apply DevOps practices, including Git, automated testing, CI/CD, infrastructure as code, and repeatable deployment across development, testing, and production environments
- Tune pipelines, Spark workloads, SQL queries, and compute configurations to improve performance, scalability, and cost efficiency
- Own the investigation and resolution of platform incidents and pipeline failures; perform root-cause analysis and implement preventive improvements
- Partner with infrastructure teams on backup, recovery, and business continuity procedures, and maintain operational documentation and runbooks
- Conduct code and design reviews, establish engineering standards, and mentor engineers across internal and vendor teams
Skills
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
- 5+ years of data engineering experience building and supporting enterprise data platforms and pipelines
- 3+ years of hands-on experience with Databricks in production environments
- Strong proficiency in Python, PySpark, SQL, and Apache Spark
- Experience with Delta Lake and modern lakehouse architectures
- Hands-on experience with Azure data services and cloud-based data platforms
- Strong knowledge of data modeling, relational databases, and ETL/ELT best practices
- Experience integrating enterprise databases and APIs into scalable data solutions
- Experience with Git, CI/CD pipelines, and automated deployment practices
- Proven ability to monitor, troubleshoot, and optimize data pipelines and platform performance
- Demonstrated leadership in solution design, code reviews, mentoring, and cross-functional collaboration
- Strong problem-solving and communication skills
- Experience administering and optimizing Databricks environments, including Unity Catalog
- Experience with PostgreSQL, GraphQL APIs, and operational applications leveraging lakehouse data
- Healthcare data experience, including claims, eligibility, provider, or clinical datasets
- Familiarity with healthcare interoperability standards such as HL7, FHIR, and X12
- Experience with Terraform or other infrastructure-as-code tools
- Experience with streaming data pipelines and event-driven architectures
- Experience supporting AI, machine learning, or NLP data workloads
- Familiarity with regulated data environments and governance best practices
- Experience with cloud data platform migrations and modernization initiatives
- Azure, Databricks, or AWS certifications preferred
Benefits
- This position is remotely based in the U.S.
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