JPMorgan ChaseData & AnalyticsOfficial Job Posting

Data Management Associate at JPMorgan Chase

Bengaluru, KarnatakaHybrid0–3 YearsNot specified

JPMorgan Chase Hiring Data Management Associate\n\nJPMorgan Chase & Co. is a leading global financial services firm. As part of our expanding digital bank initiatives, we are looking for a Data Management Associate to oversee data governance, maintain data quality, and optimize data assets across enterprise systems. Candidates will work closely with engineering, compliance, and analytics teams to enforce high standards of data integrity and accessibility.

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JPMorgan Chase Data Management Associate career opportunity

Official Role Details

Role Overview

JPMorgan Chase Hiring Data Management Associate\n\nJPMorgan Chase & Co. is a leading global financial services firm. As part of our expanding digital bank initiatives, we are looking for a Data Management Associate to oversee data governance, maintain data quality, and optimize data assets across enterprise systems. Candidates will work closely with engineering, compliance, and analytics teams to enforce high standards of data integrity and accessibility.

Applicant Requirements

Eligibility Criteria & Qualifications

Degree / QualificationB.E / B.Tech / MCA / B.Sc

Eligible BatchesNot specified

Official Eligibility Points

Bachelor's degree in Computer Science, Data Science, Information Technology, or related discipline.
0 to 3 years of relevant experience in data management, quality assurance, or quantitative analysis.
Demonstrated familiarity with SQL, enterprise data architectures, and data lifecycle management.

Day-to-Day Deliverables

Key Responsibilities

Data Preparation & Quality

•Maintain data quality frameworks and automate validation checks across digital banking platforms.
•Ensure compliance with global regulatory standards regarding data privacy, security, and governance.

Analysis, Reporting & Visualization

•Collaborate with cross-functional technical teams to define data lineage, metadata standards, and governance rules.

Insights & Stakeholder Communication

•Perform root-cause analysis on data discrepancies and implement long-term remediation strategies.

Technical Qualifications

Required Skills & Technologies

SQLData GovernanceData ManagementData Quality AnalysisPythonMetadata ManagementRelational Databases

Official Application Method

How to Apply

Submit your application directly through JPMorgan Chase's verified careers portal.

Review the published role requirements, degree qualifications, and eligible graduation batches above.

Ensure your resume highlights relevant projects and contains working GitHub repository links.

Click the official application button below to open JPMorgan Chase's direct careers page.

Complete and submit your application directly on the employer's portal.

Apply on JPMorgan Chase Official Careers Page

You will be directed to JPMorgan Chase's official careers portal. Career Insights does not process applications or charge any candidate fees.

The specifications above are verified official details published by JPMorgan Chase. Candidates should verify all final terms, deadlines, and eligibility directly on JPMorgan Chase's official careers portal before submitting an application.

Career Insights

Recommended Preparation

Independent editorial guidance based on the published role information.

What to Prepare

Evaluate your data analysis and quantitative background against published criteria and hands-on preparation focus areas.

Education & Academic Criteria

Cohort: Eligible: Not specifiedPublished Requirement

Published Requirement

B.E / B.Tech / MCA / B.Sc

Preparation Focus

Hiring evaluations prioritize demonstrable problem-solving, domain competence, and practical project evidence over specific degree pedigree.

SQL & Data Querying

Published Requirement

Proficiency in relational databases, SQL queries, and data extraction.

Preparation Focus

Master complex SQL operations: Window functions (ROW_NUMBER, RANK, DENSE_RANK), CTEs, multi-table JOINs, and query execution plan analysis.

Data Analysis & Visualization

Published Requirement

Data cleaning, transformation, and reporting dashboards.

Preparation Focus

Be prepared to clean messy datasets using Python (Pandas/NumPy) or Excel, identify statistical outliers, and explain KPI metric definitions.

Data Storage & Persistence

Published Requirement

Familiarity with databases, schema modeling, and structured query writing.

Preparation Focus

Be prepared to explain relational normalization (1NF-3NF), indexing trade-offs, foreign key constraints, and transactional consistency.

Version Control & Engineering Hygiene

Published Requirement

Familiarity with Git branching, pull requests, and collaborative repository management.

Preparation Focus

Review Git branch workflows, pull request code reviews, and maintain clean commit history with descriptive messages.

Work Mode & Collaboration

Published Requirement

Hybrid (Bengaluru, Karnataka) operational structure.

Preparation Focus

Highlight proactive written communication, technical documentation discipline, and the ability to troubleshoot errors systematically before escalating.

Technical Topics

Depending on the hiring team’s evaluation style, technical assessments for this role typically cover these core areas:

Topic 1: Advanced SQL & Data Extraction

Preparation Topic

Window functions (ROW_NUMBER, RANK, DENSE_RANK, LAG, LEAD)
Common Table Expressions (CTEs), multi-table JOINs, and subqueries
Query optimization, index utilization, and execution plan review

Preparation Tip: Practice writing complex SQL aggregations on paper or in an editor, explaining your reasoning around NULL handling and join cardinalities.

Topic 2: Data Cleaning, Wrangling & Validation

Preparation Topic

Handling missing values, duplicated records, and date/time conversions
Using Python (Pandas/NumPy) or SQL for data hygiene and transformation
Detecting statistical outliers and verifying data distribution integrity

Preparation Tip: Explain your systematic approach to validating a raw dataset before performing any modeling or executive reporting.

Topic 3: Metric Definition, KPI Modeling & Dashboard Architecture

Preparation Topic

Designing intuitive business dashboards (Power BI, Tableau, Looker)
Formulating unambiguous metric definitions (retention, churn, cohort LTV)
Choosing appropriate data visualizations for business decision-making

Preparation Tip: Be prepared to demonstrate how you designed a dashboard so that executives can draw actionable insights within seconds rather than hunting through tables.

Topic 4: Business Problem Solving with Data & Hypothesis Testing

Preparation Topic

Formulating testable hypotheses from operational questions
Segmenting customer or operational cohorts to isolate drivers
Translating statistical patterns into concrete operational recommendations

Preparation Tip: Pick a dataset project from your portfolio and clearly articulate: what was the business question, what did the data reveal, and what decision was made.

Topic 5: Cross-Functional Storytelling & Analytical Communication

Preparation Topic

Explaining data nuances and limitations to non-technical team members
Answering questions about statistical confidence and data provenance
Collaborative iteration with product managers and engineers

Preparation Tip: Frame analytical results around business impact: revenue saved, efficiency gained, or risk avoided.

* Note: These are independent Career Insights editorial recommendations to help candidates structure their study plan. They do not represent guaranteed interview stages or official hiring mandates from JPMorgan Chase.

Practical Project

Turn the listed data skills into a portfolio exercise using a realistic dataset, analysis workflow, and decision-focused output.

Practical Project

Modular CLI Utility with Robust Error Handling

Recommended Preparation Project

What to Build

A command-line tool that automates file parsing or API data collection, featuring configurable flags, structured error logs, and comprehensive unit tests.

Skills Demonstrated

SQL, CLI Design, Error Handling, Unit Testing

GitHub Deliverables

Include clear command-line usage examples with flags, installation guide, and unit test execution command with coverage reports.

Interview Talking Points

Code structure, how edge cases are caught gracefully, and unit test coverage strategy.

Career Insights recommendation: This project is an independent editorial recommendation designed to help candidates build verifiable portfolio evidence. It is not required or sponsored by JPMorgan Chase.

Before You Apply

Verify your dataset portfolios, dashboard presentations, and application materials before applying.

1. Role-Tailored Resume & Data Portfolio Links

Ensure your resume highlights SQL queries, data manipulation projects, and interactive dashboard links involving SQL, Data Governance, Data Management.

2. Eligibility & Qualifications Verification

Confirm that your degree, graduation year (Not specified), and location match JPMorgan Chase's criteria.

3. Data Project & Metric Walkthrough Review

Have 1–2 data analysis projects prepared. Be ready to explain your data cleaning methodology, SQL aggregation queries, and actionable conclusions.

4. Direct Submission on JPMorgan Chase's Official Portal

Submit your application directly through JPMorgan Chase's official careers portal using the verified apply link below. Career Insights does not process applications or charge any candidate fees.

Career Growth Context

Editorial analysis of how this role builds quantitative expertise and strategic analytical influence.

Data Architecture & Tooling Orientation

Familiarity with enterprise data warehouses, schema design, SQL data pipelines, and internal business metrics.

Exploratory Analysis & Dashboard Engineering

Constructing performant business intelligence dashboards, validating dataset integrity, and automating recurring analytical reporting.

Statistical Modeling & Strategic Insights

Conducting cohort analyses, predictive modeling, and identifying trends that drive product, operational, or business efficiency.

Progression Toward Senior / Lead Analytics Partner

Defining data governance standards, leading cross-functional data initiatives, and guiding organizational decision-making with executive stakeholders.

Career Insights Context: Career advancement in data and analytics is driven by quantitative rigor, clear stakeholder communication, and the demonstrated ability to turn raw data into high-leverage business decisions.

Career Insights Editorial Standards

This page provides verified job details sourced from JPMorgan Chase's recruitment announcement, alongside independent preparation roadmaps authored by the Career Insights editorial team. Career Insights is not affiliated with JPMorgan Chase and does not collect candidate data or charge application fees.