> Markdown version of [/jobs/ext/4486439-lead-data-engineer](https://www.wearedevelopers.com/jobs/ext/4486439-lead-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead - Data Engineer - **Company:** Astrana Health - **Location:** United States - **Experience:** Expert - **Salary:** $170,000.0 - $240,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, ASC X12 Standards, Application Services, Automation of Tests, Microsoft Azure, Clinical Data Repository, Code Review, Databases, Continuous Integration, Data Deduplication, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Structures, Relational Databases, DevOps, Interoperability, Python (Programming Language), PostgreSQL, Machine Learning, Runbook, Software Engineering, SQL Databases, Data Streaming, Systems Integration, Enterprise Data Management, Cloud Platform System, Azure Data Factory, Fast Healthcare Interoperability Resources, System Availability, Apache Spark, Change Data Capture, Git, Event Driven Architecture, Data Lakes, Pyspark, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Health Level Seven International, Graphql, Terraform, Data Pipelines, Databricks - **Published:** October 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=020b71dc0171a209 ## About the Role * 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. ## Description We are seeking a Lead - Data Engineer to lead the hands-on design, development, and operation of key components of Astrana's enterprise data platform, including the Constellation Lakehouse, Connect API (GraphQL) layer, and Lakebase-backed applications. This role will build scalable data pipelines, integrate healthcare data sources, and develop unified data models that support analytics, reporting, AI and machine learning, and operational applications. The position combines advanced data engineering with responsibility for platform reliability, performance, security, and automation within an Azure Databricks environment. As a hands-on technical lead, you will translate complex requirements into reliable production solutions, establish engineering standards, and mentor other engineers. You will collaborate with analytics, software engineering, infrastructure, security, business stakeholders, and external vendors to advance the platform and support its growing adoption. Our Values * Put Patients First * Empower Entrepreneurial Provider and Care Teams * Operate with Integrity & Excellence * Be Innovative * Work As One Team, * 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.