Wells Fargo is Hiring Analytics Consultant in Hyderabad
Financial Crimes Analytics | Hyderabad
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Job Overview
Wells Fargo is hiring an Analytics Consultant to join its Financial Crimes Analytics team in Hyderabad. The role supports investigative teams such as Intelligence and Special Operations by identifying, extracting, and analyzing relevant information from large-scale banking and financial services data environments.
The successful candidate will work extensively with SQL, Power BI, enterprise data warehouses, customer and transaction data, and data investigation workflows. This opportunity requires deep analytical rigor to investigate data anomalies and support financial crimes, risk, compliance, and operational reporting activities.
💡 Why this role?
This is a highly impactful role that merges advanced data engineering, SQL expertise, and business intelligence within a critical compliance domain at a major global bank. It’s perfect for candidates looking to leverage analytical dashboards and data discovery to combat financial crime.
Key Responsibilities
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Write and optimize complex SQL scripts involving multiple table joins, CTEs, temporary tables, CASE statements, RANK, and QUALIFY clauses.
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Support Intelligence and Special Operations teams with accurate and timely data extracts, navigating large metadata repositories for investigations.
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Develop dashboards, visualizations, and analytical reporting solutions using Power BI to contextualize high-volume transaction and payment data.
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Ensure accuracy and completeness of analytical outputs by performing rigorous data profiling and validation on enterprise data warehouses (e.g., Teradata).
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Investigate data anomalies and potential risks, maintaining clear documentation for SQL scripts, data sources, and data lineage in adherence to governance standards.
Eligibility Criteria
Education & Experience
Candidates must hold a B.Tech in Computer Science Engineering (CSE) or Information Technology (IT) (MBA in Finance is a plus). You must have 2+ years of experience in data analysis with a strong SQL focus, alongside extensive experience with Power BI, enterprise data warehouses, and large-scale banking or financial datasets.
How to Apply
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