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Protocol Intelligence
Data-driven signals on your job's competitivenessNiche Databricks and streaming lead role with senior requirement reduces applicant density.
High because healthcare payer expertise and Databricks streaming specialization limit transferability.
High due to explicit 8+ years, required Databricks, PySpark, Kafka, and healthcare domain experience.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and optimize end-to-end data pipelines using Databricks with PySpark and Delta Lake, focusing on real-time streaming ingestion from Kafka and other event sources.
Implement layered data architecture (Bronze, Silver, Gold) for healthcare transactional data involving ingestion, validation, enrichment, and applying data quality/business rules.
Lead cloud migration efforts from on-premise to Databricks and Snowflake, drive CI/CD and DevOps practices, mentor team members, and collaborate with stakeholders for scalable delivery.
Minimum Requirements
8+ years total experience in data engineering.
3+ years hands-on experience with Databricks (streaming and batch).
Strong expertise with PySpark, Spark SQL, Spark Streaming, and real-time data streaming using Kafka.
Experience with AWS services including S3, Airflow, Lambda, and implementing CI/CD pipelines with Git automation.
Ideal Candidate Profile
Experienced in the healthcare payer domain with knowledge of claims, membership, coverage data, and familiarity with FHIR or healthcare data standards.
Proven leadership experience in tech lead or senior roles handling module ownership and team mentoring across distributed teams.
Skilled in designing and delivering scalable data engineering solutions under SLA-driven environments with security and data governance focus (PII/HIPAA).