JPMorgan Chase & Co. – Hiring for Data Analyst / Analytics Associate @ Bengaluru

Global financial services leader JPMorgan Chase & Co. (JPMC) is recruiting for a Data Analyst / Analytics Associate under Job ID: 210780424 within its Global Service Centers / Technology & Operations hubs in India (Bengaluru / Hyderabad / Mumbai).

This role focuses on leveraging modern data engineering, business intelligence, SQL analytics, and visualization frameworks to drive strategic decision-making, optimize financial workflows, and enhance operational risk controls across the bank’s lines of business.

Job Details

About Company

JPMorgan Chase & Co. (NYSE: JPM) is one of the world’s oldest and largest financial institutions, managing trillions of dollars in assets. The firm offers solutions to the world’s most important corporations, governments, and institutions in more than 100 countries.

JPMorgan Chase’s India Technology & Operations centers serve as a backbone for global business operations, risk modeling, tech development, and quantitative business analytics.

Job Description

As a Data Analyst at JPMorgan Chase, you will join a high-impact analytics team dedicated to managing large-scale financial and operational datasets. You will be responsible for creating automated data pipelines, writing complex analytical SQL scripts, building interactive executive dashboards (Tableau / Qlik / Power BI), and transforming raw transactional logs into actionable management insights.

Requirements & Qualifications

1. Educational Qualifications & Experience

• Degree: Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Technology, Statistics, Finance, or a related quantitative field.
• Experience: 1 to 5 years of professional experience in data analysis, business intelligence, or quantitative reporting (prior experience in Banking, Financial Services, or Fintech is a strong plus).

2. Core Technical Competencies

• SQL & Data Querying: Advanced proficiency in SQL (writing complex joins, CTEs, window functions, and query optimization across platforms like Oracle, Teradata, PostgreSQL, or Snowflake).
• Business Intelligence & Visualization: Demonstrated expertise in designing interactive dashboards using Tableau, Power BI, or Qlik Sense.
• Programming & Automation: Solid knowledge of Python or R for data manipulation (Pandas, NumPy), basic scripting, and data cleanup.
• Data Warehousing & ETL: Familiarity with data pipeline concepts, ETL processes, and enterprise data warehousing architectures.

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Roles and Responsibilities

1. Data Analytics & Insights Generation

• Extract, clean, and model complex financial and transactional datasets to analyze business trends, performance drivers, and operational risks.
• Develop predictive models and trend analyses to support executive business strategies.

2. Dashboarding & Executive Reporting

• Design, publish, and maintain enterprise Tableau/Power BI dashboards for regional and global senior stakeholders.
• Ensure data consistency, accuracy, and metric reconciliation across multiple line-of-business systems.

3. Automation & Process Improvement

• Automate manual daily and monthly data consolidation workflows using Python scripts, SQL procedures, and scheduled batch jobs.
• Collaborate with data engineers and enterprise architecture teams to improve data governance, pipeline scalability, and query efficiency.

Role Summary

The Data Analyst position at JPMorgan Chase is an integral analytical role within global technology and operations. Your primary objective is to turn raw financial metrics into clear, decision-ready data products that maintain compliance, optimize business performance, and reduce operational bottlenecks.

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Company Culture & Work Model

• Work Setup: Standard hybrid/office model in line with JPMorgan Chase corporate location guidelines.
• Professional Growth: Excellent learning and development ecosystem, global mobility options, and direct exposure to enterprise-level financial technologies.

Why We Recommend This Job

1. Global Tier-1 Brand: Boost your career by working for a premier global investment bank and financial institution.
2. Enterprise Scale Data: Experience handling massive, complex transactional and operational datasets with strict data governance frameworks.
3. Clear Career Path: Direct progression into Senior Analytics Lead, Quantitative Business Analyst, Data Engineering, or Product Management.

Career Growth Potential

Data Analyst (Req 210780424) ➔ Senior Analytics Associate ➔ Lead Data Scientist / Analytics Manager ➔ Vice President (VP) - Data & Analytics

Skills You’ll Gain

Salary & Benefits Info

• Compensation: Highly competitive corporate compensation benchmarked against top-tier financial centers in India (typically ₹8.5 LPA to ₹18 LPA depending on candidate experience level and title band).
• Benefits: Full medical and life insurance coverage, retirement plans (PF, Gratuity), tuition reimbursement, and wellness programs.

How to Apply?

1. Click on the official application link below.
2. Verify the Job Title (Data Analyst) and Job ID (210780424).
3. Click on Apply Now on the JPMorgan Chase Oracle Cloud candidate portal.
4. Sign in to your account or register as a new candidate.
5. Upload your updated Resume/CV highlighting your experience with SQL, Python, and Tableau/Power BI.
6. Submit your application.

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Frequently Asked Interview Questions (With Answers & Solution Guidelines)

1. SQL Window Functions for Analytical Queries
   • Question:“How do you calculate a 3-month rolling average of customer transaction amounts in SQL?”
   • Answer Strategy: Detail using window functions:AVG(transaction_amount) OVER (PARTITION BY customer_id ORDER BY transaction_date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW).
2. Dashboard Performance Optimization
   • Question:“How do you optimize a slow-loading Tableau or Power BI dashboard connected to millions of records?”
   • Answer Strategy: Discuss creating optimized database views or extracts, reducing unnecessary quick filters, minimizing calculated fields at the visual level by pre-aggregating in SQL/ETL, and leveraging indexing in the underlying database.
3. Data Quality & Reconciliation
   • Question:“What steps do you take when source system numbers do not match your analytical reporting database?”
   • Answer Strategy: Outline a systematic reconciliation workflow: 1) Verify boundary filters and time zone alignments; 2) Check for duplicate records using unique keys; 3) Inspect recent ETL log errors; 4) Perform row-by-row sampling using SQL comparisons.