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Tier-1 employer, metro locations, and a generalist Data Engineer title increase candidate density.
Platform-focused Databricks, AWS and Spark skills are broadly transferable across industries.
Explicit 8+ years plus mandatory Databricks/AWS/Spark/Python/platform experience creates highly selective filters.
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Lead and support the migration, onboarding, and maintenance of data pipelines on a Databricks-on-AWS lakehouse platform ensuring reliability and performance.
Provide technical guidance and delivery oversight to a small offshore engineering team for enterprise data platform operations.
Implement and uphold engineering best practices for cloud-native data ingestion, transformation, monitoring, and governance using AWS and Databricks services.
Minimum 8+ years of experience in data engineering or related roles.
Proven expertise with Databricks or similar cloud data platforms and AWS data engineering services (Amazon S3, AWS Glue, AWS IAM).
Hands-on skills in Spark, SQL, Python, and familiarity with data governance and lakehouse technologies such as Delta Lake and Unity Catalog.
Work Experience Required: 8+ years in data engineering roles
Experienced in enterprise-scale cloud data platform delivery with strong understanding of AWS and Databricks lakehouse ecosystems.
Capable of technical leadership for offshore teams with focus on operational excellence, CI/CD, and secure, governed data workflows.
Skilled in integrating metadata, data quality, security, and governance controls within cloud data pipelines and data onboarding processes.