DataBricks Developer - Remote

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Job Description

Key Responsibilities

• Design and implement end-to-end Databricks Lakehouse architectures for healthcare data platforms.
• Define data architecture patterns for batch and real-time data processing.
• Design ingestion frameworks for healthcare data from EHR/EMR, claims, clinical, pharmacy, lab, HL7, FHIR, APIs, and other sources.
• Develop scalable data pipelines using Apache Spark, PySpark, Delta Lake, Delta Live Tables/Lakeflow, and Databricks Workflows.
• Design and implement Medallion Architecture (Bronze, Silver, and Gold layers).
• Implement data governance, cataloging, lineage, and fine-grained access controls using Unity Catalog.
• Ensure architecture and data processing practices support HIPAA, PHI, PII, and other healthcare security and compliance requirements.
• Optimize Databricks workloads for performance, scalability, reliability, and cost.
• Define data modeling strategies for analytics, reporting, population health, clinical analytics, and AI/ML use cases.
• Collaborate with healthcare business stakeholders, data engineers, data scientists, analysts, security, compliance, and enterprise architecture teams.
• Establish architecture standards, best practices, coding standards, and reusable frameworks.
• Lead technical design reviews and provide mentorship to data engineering teams.
• Support CI/CD, DevOps, infrastructure automation, and deployment strategies for Databricks environments.

Required Technical Skills

• Strong hands-on experience with Databricks Lakehouse Platform.
• Expert knowledge of Apache Spark and PySpark.
• Strong experience with Delta Lake, Delta Live Tables/Lakeflow, Databricks Workflows, and Databricks SQL.
• Experience with Unity Catalog, data governance, data lineage, RBAC, and access control.
• Strong SQL and Python skills.
• Must have strong Healthcare Experience/ Strong Databricks/ Healthcare Experience with one or more cloud platforms:
  • Azure Databricks / ADLS / Azure Data Factory
  • AWS Databricks / S3 / Glue / Lambda
  • Google Cloud Platform Databricks / GCS / Pub/Sub
• Experience designing batch and streaming data pipelines.
• Experience with Git, CI/CD, Terraform, and DevOps practices.