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Recognized employer, common mid-level Data Analyst title, and broad skill requirements increase applicant competition.
Core SQL, ETL and data-quality skills are broadly transferable, though healthcare and web-analytics experience favors similar industries.
Requires explicit 4+ years plus expert SQL, DB and ETL/reporting skills, creating stringent shortlisting filters.
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Drive analysis and define requirements for multiple data quality projects impacting business units in Health and Legal sectors.
Document and map complex organizational data flows, leveraging AI tools to improve clarity and automation.
Collaborate with diverse teams (Business Intelligence, Finance, Marketing, Sales) to capture and validate data quality needs and build enterprise-wide data quality validation inventories.
4+ years of hands-on experience with database technologies including PostgreSQL, Vertica, GBQ, DorisDB.
Expert-level proficiency in SQL and experience with ETL tools like Pentaho and Informatica.
Experience with AI tools (Google Gemini, Claude, GEMS, prompt engineering) relevant to data quality and business use cases.
Excellent documentation, system diagramming (MIRO/Visio), and communication skills required.
Experienced in working cross-functionally with both technical and non-technical teams to translate complex data concepts effectively.
Background combining advanced AI tooling proficiency with strong SQL/database skills suited for building and validating complex data quality systems.
Demonstrated ability to take ownership on enterprise data integration and analytics projects with a focus on data quality and automation.