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Popular mid-level data engineer role with hybrid/metro context increases applicant competition.
Core data engineering skills (Python, SQL, Spark) are highly transferable across industries.
Explicit 2–4 years requirement plus mandatory Python, SQL, Spark and client-project experience enforces strict filters.
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Develop, maintain, and troubleshoot data pipelines and engineering solutions handling large datasets.
Provide technical and production support for client-based projects, resolving technical issues and delivering solutions.
Monitor, troubleshoot, and optimize data workflows and pipelines to ensure efficient operation.
2–4 years of relevant Data Engineering experience.
Strong hands-on experience with Python, SQL, and Spark.
Prior experience working on client-based projects is mandatory.
Work Experience Required: 2–4 years; Notice period: Not explicitly mentioned in the JD.
Experienced in balancing technical development with client/project support roles.
Skilled in troubleshooting and optimizing production data workflows in a client-facing environment.
Familiarity or experience with Databricks and AWS Cloud is preferred but not mandatory.