
at J.P. Morgan
Bulge Bracket Investment BanksPosted 14 days ago
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**Data Owner Senior Associate** in Bengaluru, India drives data excellence through strategic ownership and technical innovation. In this role, you'll enable end-to-end data creation, ingestion, publishing, and consumption. Key responsibilities include defining product data, monitoring quality, coordinating delivery, and ensuring governance compliance. Quantitative analysis skills in SQL are essential, along with the ability to thrive in fast-paced environments and effectively communicate with diverse stakeholders. Requirements include a Bachelor's degree and 6+ years of experience in data delivery, analytics enablement, or governance roles. Preferred candidates possess experience in financial services, wealth management, or CRM data domains, and proficiency in Python or ETL tools.
- Compensation
- Not specified
- City
- Bengaluru
- Country
- India
Currency: Not specified
Full Job Description
Location: Bengaluru, Karnataka, India
Data Owners are needed to drive data excellence through strategic ownership and technical innovation.
As a Data Owner Senior Associate within Consumer & Community Banking - Data & Analytics team, you will be responsible for end-to-end enablement, publishing, and governance for all data created. You help define and document product databusiness definitions, metadata, classifications, and quality expectationsso it is discoverable, understood, and fit for purpose. You assist with monitoring, issue management, and cross-functional coordination to improve data quality and reduce data risk across the lifecycle.
Job responsibilities
Support the products data agenda across creation, ingestion, publishing, and consumption
Assist in establishing data quality requirements and monitoring for accuracy, completeness, timeliness, and lineage.
Support delivery of data pipelines and products by tracking dependencies, coordinating handoffs, and reinforcing Agile execution across workstreams.
Document business definitions, metadata, and classifications so critical data is discoverable and consistently understood
Maintain data governance artifacts such as inventories, controls evidence, and procedures to support ongoing compliance and audit readiness
Perform data profiling and validation to identify anomalies, gaps, and trends impacting downstream use
Partner with technology and data delivery teams to support root cause analysis and remediation execution
Communicate updates, risks, and decisions through well-structured documentation and stakeholder routines.
Contribute to continuous improvement by identifying process bottlenecks and proposing pragmatic fixes
Required qualifications, capabilities, and skills
Bachelors degree with 6+ years of experience in data delivery, analytics enablement, data governance, or adjacent roles
Proficient in SQL to analyze data, validate quality, and support investigations across relational or big data platforms
Demonstrate ability to execute reliably in a fast-paced, stakeholder-rich environment with clear follow-through
Communicate effectively with both technical and non-technical partners via written updates and presentations.
Think analytically, breaking down ambiguous problems into actionable steps and measurable outputs
Manage multiple priorities with strong organization, attention to detail, and time management
Learn quickly and apply feedback to improve deliverables and operating routines.
Preferred qualifications, capabilities, and skills
Bring experience in financial services, wealth management, or client/advisor data domains
Utilize data catalogs, lineage tools, and data quality monitoring solutions
Apply experience working with Agile teams and participating in ceremonies (planning, standups, retrospectives, etc.)
Leverage exposure to CRM and sales platforms (e.g., Salesforce) and related data flows
Use Python or ETL tooling for profiling, wrangling, and repeatable data quality checks
Demonstrate understanding of data governance, data ethics, and responsible data use in regulated environments
Embrace a growth mindset and continuous learning of modern data patterns and tooling




