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Popular Data Engineer role in metro with moderate brand, Databricks focus narrows but candidate density remains medium.
Core data engineering skills transferable, but Databricks-specific requirements raise industry specificity to medium.
Explicit 7–9 years and mandatory Databricks lakehouse skills (Unity Catalog, DLT) increase filtering strictness.
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Design, build, and optimize large-scale data pipelines and lakehouse solutions using Databricks.
Apply the latest Databricks platform features, including Unity Catalog, Lakeflow (Delta Live Tables), and Lakebase, to solve data engineering challenges.
Leverage expanding AI/agent tooling in Databricks to enhance data engineering workflows.
7 to 9 years of experience in data engineering or related roles.
Strong expertise with Databricks platform and its components (Unity Catalog, Lakeflow, Lakebase).
Work Experience Required: 7 to 9 years.
Educational or location requirements: Not explicitly mentioned in the JD.
Deep hands-on experience as an individual contributor on complex data engineering projects at scale.
Up-to-date knowledge of Databricks innovations and ability to implement cutting-edge features effectively.
Experienced in architecting and optimizing data lakehouse environments with a focus on performance and scalability.