JPMorgan Chase – Data Management Associate

The Data Management Associate position at JPMorgan Chase is an opportunity for professionals interested in data management, data governance, analytics, reporting, and enterprise data solutions to work within one of the world's leading financial institutions. Based in Bengaluru, the role supports data-driven initiatives where accurate, reliable, and well-governed information is essential for business decision-making. The position involves working with product and business teams to understand requirements, analyze data, deliver accurate reports, and develop solutions that address business needs. As part of JPMorgan Chase's data organization, the associate contributes to technology and analytics initiatives designed to make enterprise data more trusted, accessible, and useful while supporting the firm's broader data management and governance objectives.

A core focus of the role is translating business and product requirements into data-driven solutions and analytical outputs. The associate may work with large datasets, investigate data-quality issues, support reporting requirements, and collaborate with stakeholders to ensure that information is accurate and fit for purpose. Depending on the assigned team, the work can involve SQL, Python, data analysis tools, reporting platforms, data warehouses, and data governance processes. The position also requires strong analytical thinking because data management teams frequently need to identify inconsistencies, troubleshoot issues, understand data relationships, and determine how information should be structured and governed. Working within an agile environment, the associate contributes to the design and delivery of secure, stable, and scalable data solutions that support JPMorgan Chase's business objectives.

The role also provides exposure to enterprise data governance, data risk management, data quality, and cross-functional collaboration. Data management professionals work with product teams, technology groups, business stakeholders, and other specialists to establish reliable processes and improve the way organizational data is managed. Depending on the business function, responsibilities can extend to data warehouse initiatives, process engineering, reporting, issue resolution, and continuous improvement. Strong communication and stakeholder-management skills are therefore as important as technical data skills. For professionals looking to build a career in financial-services analytics, data governance, business intelligence, or data management, this position offers experience working with large-scale enterprise data in a highly structured and technology-driven banking environment.

Roles & Responsibilities

1. Analyze Business Requirements
   Work with product and business teams to understand data requirements, clarify reporting needs, identify expected outcomes, and translate business problems into practical data solutions.
2. Support Data Product Delivery
   Contribute to the development and delivery of data products, analytics solutions, and reporting capabilities that support business functions and organizational objectives.
3. Perform Data Analysis
   Analyze large and complex datasets to identify trends, inconsistencies, relationships, and insights that can support business decisions and improve data-driven processes.
4. Maintain Data Quality
   Investigate data-quality issues, identify inconsistencies or gaps, perform validation activities, and work with relevant teams to improve the accuracy and reliability of enterprise data.
5. Develop Data Solutions
   Assist in designing and implementing data-driven solutions that meet defined business requirements while following established technology, security, and data-management standards.
6. Support Data Governance
   Contribute to data governance initiatives by helping maintain data definitions, ownership structures, controls, standards, and processes designed to improve enterprise data management.
7. Build Reports & Analytics
   Develop accurate reports and analytical outputs using appropriate data sources and analytical tools while ensuring that results are consistent with business requirements.
8. Work With SQL & Python
   Use SQL and Python where required to query, manipulate, analyze, validate, and process data for reporting, troubleshooting, automation, and analytical use cases.
9. Support Data Warehouse Initiatives
   Participate in data warehouse-related activities, including requirements gathering, data analysis, testing, implementation support, and ongoing business or operational support.
10. Troubleshoot Data Issues
    Apply critical thinking to investigate data or process problems, determine root causes, recommend solutions, and coordinate with relevant technology or business teams.
11. Collaborate in Agile Teams
    Participate in agile delivery practices and work with geographically distributed teams to plan, develop, test, and deliver data solutions in a structured environment.
12. Drive Continuous Improvement
    Identify opportunities to improve data processes, reporting workflows, analytical capabilities, and operational efficiency while contributing ideas that create measurable business value.

Requirements & Eligibility

1. Relevant Educational Background
   Candidates should have a bachelor's degree or equivalent qualification in Computer Science, Information Technology, Data Analytics, Business Analytics, Engineering, Mathematics, or another relevant discipline.
2. Data Management Experience
   Candidates should have relevant experience in data management, data analytics, business intelligence, reporting, data governance, or a related field, with the exact experience requirement depending on the specific team and position level.
3. SQL Proficiency
   Strong SQL knowledge is valuable for querying relational databases, joining datasets, validating information, investigating data issues, and producing analytical outputs.
4. Python Knowledge
   Familiarity with Python is beneficial for data analysis, automation, data manipulation, validation, and developing repeatable solutions for data-related workflows. Some versions of the role specifically identify Python as a required or preferred capability.
5. Data Governance Understanding
   Candidates should understand fundamental data governance concepts such as data ownership, data quality, data definitions, controls, standards, lineage, and responsible management of enterprise information.
6. Data Analysis Skills
   Strong analytical abilities are required to work with large datasets, identify patterns and anomalies, investigate data problems, and convert raw information into meaningful business insights.
7. Reporting & BI Tools
   Exposure to tools such as Power BI, BusinessObjects, Alteryx, Excel, or comparable analytics and reporting platforms can be advantageous depending on the assigned data-management function.
8. Agile & Project Collaboration
   Experience working in Agile environments, including Scrum or Kanban, is beneficial for collaborating with product teams, technology teams, and other stakeholders throughout the data solution lifecycle.
9. Problem-Solving & Communication
   Candidates should demonstrate strong critical thinking, attention to detail, communication, stakeholder-management, and troubleshooting skills to effectively investigate issues and explain data-related findings.
10. Financial Services Awareness
    An understanding of banking, financial services, risk, compliance, or enterprise data environments can be beneficial, particularly when working with data that supports business, regulatory, or risk-management decisions.

Expected Salary

Glassdoor's current estimate for a JPMorgan Chase Data Management Associate in Bengaluru is approximately ₹6 lakh–₹9 lakh per annum. However, salary data for the broader JPMorgan Chase Data Management Associate title varies considerably by experience and business function, so the actual compensation can differ substantially.

For this Bengaluru opportunity, a realistic expected salary range is approximately ₹6 lakh–₹10 lakh per annum, with experienced candidates possessing strong SQL, Python, data governance, analytics, and financial-services knowledge potentially commanding higher compensation. This is a market-based estimate and not an officially disclosed salary for the specific opening.

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