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Strong employer brand, metro location, mid-level generalist data role increases candidate competition.
Core SQL, ETL and BI skills are broadly transferable across industries, so low sensitivity.
Explicit 3+ years and mandatory SQL/Spark/Unix plus ETL exposure create strict technical filters.
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Write and optimize SQL and Spark SQL queries for data extraction, analysis, and reporting.
Support ETL setup, data validation, and perform data quality checks including root cause analysis.
Collaborate with cross-functional teams to deliver high-quality data solutions and troubleshoot issues using Java logs.
3+ years of experience in SQL, Spark SQL, and Unix commands.
Exposure to ETL tools and data pipeline concepts.
Basic understanding of cloud platforms like GCP or AWS (preferred but beneficial).
Bachelor’s degree in Computer Science, Information Technology, or related field required.
Experienced in building and maintaining data pipelines and performing data quality validations in hybrid cloud environments.
Comfortable collaborating with technical and non-technical teams to translate requirements into data solutions.
Able to analyze Java logs for troubleshooting indicating familiarity with back-end data processes.