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Tier-1 brand, mid-level generalist product role, metro location, and broad data skill requirements increase competition.
Product and data skills are transferable, but payments/financial services preference raises domain sensitivity.
Explicit 2–5 years plus mandatory SQL/Python and product/data governance requirements increase strictness.
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Support product operations including go-to-market planning, user onboarding, platform maintenance, and continuous improvement of data quality and insights delivery.
Drive data governance initiatives such as defining data quality standards, validation frameworks, and monitoring mechanisms to ensure accuracy and reliability.
Leverage SQL and Python for data analysis, validate product outputs, automate recurring reporting, and coordinate cross-functional discussions on product data insights and performance metrics.
2–5 years related work experience, preferably in Financial Services, Payments, or Data Analytics domains.
Strong SQL skills including joins, aggregations, and data validation queries (mandatory).
Working knowledge of Python for data manipulation, automation, and analysis (pandas, numpy) (mandatory).
Bachelor’s degree in business, data science, information technology, or equivalent work experience.
Experience in agile product management focused on analytical products and business intelligence solutions with hands-on operational involvement.
Proven ability to manage data governance frameworks and automate product operations using AI tools including GitHub Copilot and MS Copilot.
Strong cross-functional collaboration skills with experience coordinating between product, engineering, data, and sales teams to drive data integrity and product enhancements.