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Mid-level seniority, metro location, and popular data engineer title create high competition.
Databricks and cloud data engineering skills are transferable across industries but remain domain-specific.
Explicit 6–8 years plus mandatory Databricks, Delta Lake, Unity Catalog and AWS skills.
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Design and develop scalable batch and real-time data pipelines using Databricks, PySpark, and SQL.
Implement data governance and access controls via Unity Catalog and build cloud-based data solutions on AWS.
Optimize data platform performance and mentor team members while collaborating with stakeholders to deliver technical data solutions.
6–8 years of Data Engineering experience.
Strong hands-on experience with Databricks, Delta Lake, Unity Catalog, PySpark, and SQL.
Experience with AWS cloud services such as S3, IAM, Lambda, EC2, and Redshift.
Bachelor’s or Master’s degree in BE/B.Tech/M.Tech/MCA or equivalent.
Experienced in designing scalable batch and streaming data architectures in cloud environments.
Proficient in translating business requirements into optimized technical data solutions and mentoring junior engineers.
Skilled at implementing data governance frameworks and optimizing data workloads for performance and cost efficiency.