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JPMorgan Chase & Co.

Data Engineer III

JPMorgan Chase & Co. Bengaluru, Karnataka, India

Financial Services · 10,001+ employees

6 h ago Closes in 1d
data-engineer Mid (2-5 yrs) Full-time India
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About the role

The role involves designing and maintaining secure, scalable data pipelines and architectures to support business objectives. You will also utilize AI-assisted tools to accelerate analysis and ensure data integrity through rigorous control validation.

What they look for

Data Engineering SQL NoSQL Data Pipelines Data Modeling Statistical Data Analysis AI-assisted Development SDLC Data Lifecycle Control Validation Auditability Resiliency Security Agile Methodology

Requirements

Candidates must have at least 3 years of applied experience in data engineering and a strong understanding of the data lifecycle. Proficiency in advanced SQL, NoSQL databases, and statistical analysis is required, along with the ability to validate AI-generated outputs.

Full description

Be part of a dynamic team where your distinctive skills will contribute to a winning culture and team.

As a Data Engineer III at JPMorgan Chase within the Commercial & Investment Bank, you serve as a seasoned member of an agile team to design and deliver trusted data collection, storage, access, and analytics solutions in a secure, stable, and scalable way. You are responsible for developing, testing, and maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

  • Supports review of controls to ensure sufficient protection of enterprise data
  • Uses enterprise-authorized AI capabilities within the work environment to accelerate data pipeline/design analysis and documentation, validating outputs and handling data according to sensitivity and security requirements.
  • Responsible for making configuration and customization changes to generate a product at business or customer requests and advising colleagues in requests
  • Updates logical or physical data models based on new use cases
  • Frequently uses SQL and understands NoSQL databases and their niche in the marketplace
  • Applies reuse-first, AI-assisted practices to strengthen SDLC-quality routines for data pipelines (e.g., test generation and control validation), ensuring traceability/auditability and alignment to resiliency and security expectations.

Required qualifications, capabilities, and skills

  • Formal training or certification on data engineering concepts and 3+ years applied experience
  • Experience across the data lifecycle
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data engineering workflows with strong validation habits and awareness of data sensitivity.
  • Ability to review and validate AI-assisted outputs (e.g., query suggestions, test ideas, or model change summaries) before use, escalating when uncertain and following data handling requirements.
  • Advanced SQL skills (e.g., joins and aggregations) and working understanding of NoSQL databases
  • Significant experience with statistical data analysis and able to determine appropriate tools and data patterns to perform analysis
  • Experience customizing changes in tools to generate product outputs

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