Data Analytics Role

JPMorgan Chase’s interview process typically starts with an online assessment focusing on coding (Python/SQL) and aptitude. Successful candidates move to a technical interview that probes data manipulation, finance concepts, and problem‑solving abilities. The final HR round evaluates cultural fit, communication skills, and motivation. Preparation should include mock coding tests, finance basics, and clear articulation of past projects.

JPMorgan Chase promotes a collaborative environment where learning and innovation are encouraged. Employees benefit from structured career growth programs, mentorship, and a balanced work‑life approach supported by flexible policies.

Bachelor’s degree in Engineering, Science, Commerce or related fields; minimum 60% aggregate (or CGPA 6.0/10); graduating batch 2024‑2026; no active backlogs at the time of joining; strong analytical mindset and willingness to learn finance concepts.

Round 1: Online Assessment (coding and aptitude) → Round 2: Technical Interview (SQL/Python and finance domain) → Round 3: HR Interview (fit and motivation)

JPMorgan Chase & Co. is a global financial services firm with a presence in more than 100 countries. In India, the bank has built a strong foothold across retail banking, corporate finance, and technology-driven solutions. The Bengaluru office serves as a hub for data‑driven finance operations, supporting the bank’s worldwide network with cutting‑edge analytics, risk management, and reporting capabilities. The company’s culture emphasizes collaboration, continuous learning, and a commitment to delivering innovative financial products that empower clients worldwide. The Data Analytics Role is designed for fresh talent eager to dive into finance‑focused data engineering and analysis. As a member of the Finance Analytics team, you will bridge legacy data systems and modern cloud platforms, ensuring that critical occupancy cost and branch network metrics are accurate, timely, and actionable. You will work closely with finance partners, data engineers, and business stakeholders to translate complex data challenges into clear, business‑oriented insights. Key Responsibilities: 1. Gather, extract, and prepare branch network and occupancy cost data from legacy sources and Databricks for finance reporting and analysis. 2. Develop and maintain robust SQL queries and Python‑based workflows for recurring reports, ad‑hoc analysis, and data validation. 3. Document data definitions, business rules, and source‑to‑target mappings to support the legacy‑to‑Databricks transition. 4. Perform reconciliations between legacy outputs and Databricks datasets, investigate variances, and track issue resolution. 5. Translate finance partners’ questions into analytical requirements and deliver explainable outputs aligned with finance definitions. 6. Contribute to dashboards and visualisations (e.g., ThoughtSpot) and assist in automating manual reporting processes. 7. Apply data governance standards, including documentation, validation checks, and change traceability. 8. Identify opportunities for process improvement and implement automation tools to reduce manual effort. 9. Collaborate with cross‑functional teams to ensure data quality and consistency across multiple systems. 10. Support the creation of analytical documentation and training material for end‑users. Tech Stack: SQL, Python, Databricks, ThoughtSpot, Microsoft Excel, Intelligent Automation tools, Git, and basic cloud concepts (AWS/GCP). Growth Path: Starting as a Data Analyst, you can progress to Senior Analyst, Finance Data Engineer, and eventually Finance Analytics Manager, with exposure to global finance operations and leadership opportunities. Why Join JPMorgan Chase? The firm offers a vibrant learning environment, mentorship from industry veterans, and the chance to work on high‑impact financial data projects that shape global banking strategies. Competitive compensation, robust benefits, and a culture that values diversity and inclusion make it an ideal launchpad for a data‑driven finance career.