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Niche Databricks streaming lead with specialized skills and strong employer brand increases candidate competition moderately.
Strong Databricks/streaming skills transferable, but healthcare payer experience and FHIR/HIPAA preference raise domain specificity moderately.
Explicit 8+ years and 3+ years Databricks plus mandatory streaming and cloud skills make filters strict.
Design and develop end-to-end Databricks data pipelines including real-time streaming ingestion using Kafka.
Lead and own modules independently while mentoring team members, ensuring design, development, and delivery quality.
Support cloud migration from on-premise to Databricks and Snowflake, optimizing pipelines for SLA-driven performance and implementing CI/CD pipelines.
8+ years of experience in Data Engineering with 3+ years hands-on experience in Databricks.
Strong expertise in PySpark, Spark SQL, Spark Streaming, and real-time data streaming using Kafka.
Experience with AWS services including S3, Airflow, Lambda and CI/CD deployment automation tools.
Domain experience in Healthcare Payer (Claims, Membership, Coverage) with understanding of data privacy and governance (PII/HIPAA).
Experienced at managing leadership responsibilities at Lead or Senior Tech Lead levels within distributed team environments.
Deep technical proficiency in Databricks and streaming data architectures, with a proven track record in building scalable, SLA-compliant pipelines.
Background in healthcare data engineering projects involving data modeling, compliance with healthcare standards (FHIR preferred) and complex data transformation workflows.