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Popular mid-level data role in a metro with broad tool requirements and mid experience, driving high competition.
Core analytical and tooling skills transfer across industries, though fintech experience is preferential.
Explicit 3–5 years plus mandatory SQL, Snowflake, BI and Python requirements increases shortlisting strictness.
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Analyze large structured and unstructured datasets to deliver actionable insights driving strategic decisions across Product, Risk, Operations, and Business teams.
Design, build, and maintain dashboards and automated reports using Tableau, SQL, and Python to monitor KPIs and improve reporting efficiency.
Collaborate with engineering and business teams to ensure data quality, develop reusable datasets, and support data governance and analytical workflow optimization.
3-5 years of experience as a Data Analyst or in a similar analytical role.
Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Economics, Engineering, Information Systems, or related quantitative discipline.
Strong SQL skills including complex joins, CTEs, window functions, stored procedures, and performance optimization.
Hands-on experience with Snowflake or other modern cloud data warehouses; Python for data analysis and automation.
Experience working in fintech, banking, lending, financial services, or technology companies, with domain knowledge supporting financial analytics.
Proven ability to translate business requirements into analytical solutions and communicate technical findings clearly to non-technical stakeholders.
Operates effectively in a cross-functional environment partnering with Product, Engineering, Finance, and Operations teams to enhance data-driven decision-making and reporting automation.