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Tier-1 brand, mid-level data role in metro with generalist requirements increases candidate competition.
Skills are broadly transferable across industries for cloud data engineering and lakehouse platforms.
Explicit 5+ years plus mandatory Databricks, Spark, AWS and governance skills tighten shortlisting.
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Lead migration and ongoing support of data pipelines within a Databricks-on-AWS lakehouse environment, ensuring reliable and scalable operation.
Manage and mentor a small offshore team in onboarding new data assets using standardized, governed lakehouse patterns with AWS and Databricks tools.
Maintain platform integration, operational excellence, and deployment automation including incident resolution, monitoring, and compliance within AWS cloud and Databricks frameworks.
Minimum 5+ years of experience in data engineering or related pipeline development roles.
Hands-on expertise with Spark, SQL, Python, Databricks, and AWS data engineering services including Amazon S3, AWS Glue, and AWS IAM.
Familiarity with Delta Lake, Databricks Unity Catalog, and cloud-native best practices including CI/CD and infrastructure as code.
Work Experience Required: 5+ years experience explicitly stated; No explicit mention of mandatory degree or notice period.
Experienced in enterprise-scale data platform migration and operational support in a cloud-native AWS environment with Databricks lakehouse architecture.
Practitioner of data governance, secure access control, and metadata-driven onboarding workflows ensuring compliance and scalability.
Demonstrated capability in leading offshore teams delivering complex data engineering functions with strong technical mentoring and cross-team collaboration.