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Tier-1 brand, generalist Data Analyst title, metro location, and mid-seniority increase applicant competition.
Core data engineering and governance skills are transferable, but banking risk/control context increases domain specificity.
AVP-level title plus required data governance, pipelines, and leadership responsibilities make screening moderately strict.
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Lead analysis of data quality, lineage, and controls issues to recommend improvements for data integrity.
Design and build automated data pipelines and interactive dashboards to support business decision-making.
Apply advanced analytics and ML/AI techniques to large datasets to extract actionable insights and drive operational improvements.
Experience creating source-to-target mapping documents for data integration projects.
Proficiency in SQL for data validation and analysis.
Basic understanding of Data Virtualization, data-as-a-product mindset, and data mesh concepts.
Work Experience Required: Not explicitly mentioned in the JD
Experienced in data pipeline design and building automated data processing workflows in a business context.
Skilled at translating complex analytical findings into actionable business recommendations, influencing decision-making.
Able to communicate complex information clearly and influence stakeholders across functions and leadership levels.