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Strong employer brand, mid-level generalist analytics title, metro location, and common SQL/PowerBI skillset increase competition.
Role requires banking transaction/account domain knowledge and financial-crimes context, limiting cross-industry portability.
Explicit 2+ years, mandatory advanced SQL, Power BI, Teradata, and banking/financial-crimes domain make filters stringent.
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Support financial crimes investigative units by extracting and delivering accurate data from large metadata repositories.
Write, optimize, and document complex SQL scripts involving multiple joins, CTEs, and performance optimization.
Collaborate with Financial Crimes teams to understand data needs and maintain data accuracy and completeness in outputs.
Minimum 2+ years of data analysis experience with strong SQL expertise, including complex joins, CTEs, and performance tuning.
B.Tech in Computer Science or IT required; MBA in Finance is a plus; other qualifications acceptable with strong retail banking and SQL experience.
Extensive Power BI experience for dashboards and reporting from enterprise-scale banking data environments.
Experience with large-scale banking or financial services datasets; Teradata experience is required.
Experienced in querying and analyzing transaction, customer, and account-level data to support financial crime investigations and risk management.
Operates effectively in high-volume, enterprise data warehouse environments with knowledge of retail and corporate banking data.
Detail-oriented with investigative mindset and ability to proactively identify data anomalies and escalate risks.