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Lead Software Engineer - Python, ETL, GLUE, Spark, AWS.

JPMorganChase

JPMorganChase

Software Engineering
Bengaluru, Karnataka, India
Posted on Mar 23, 2026

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorganChase within the consume and community banking- JPMWM you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
  • Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
  • Adds to team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 3+ years applied experience
  • Design and implement end-to-end ETL/ELT pipelines on AWS using AWS Glue (PySpark) and/or EMR/EMR Serverless.
  • Build and maintain data lakes/lakehouses on Amazon S3 using columnar formats (Parquet/ORC) with effective partitioning, compaction, and schema evolution via Glue Data Catalog.
  • Orchestrate workflows with AWS Step Functions and/or Airflow (MWAA), including error handling, retries, and idempotency.
  • Optimize Spark jobs using best practices (predicate pushdown, broadcast joins, AQE, file sizing, caching) and monitor performance with CloudWatch and Spark UI.
  • Implement data quality checks and observability , SLAs/SLOs, and lineage/metadata practices & y, scalability, and cost; produce clear documentation and runbooks.
  • Enforce security and compliance: IAM least-privilege, KMS encryption, VPC endpoints/private networking, Secrets Manager/Parameter Store, Lake Formation access controls.
  • Collaborate on data modeling (dimensional/star, data vault, wide tables) and interface contracts for analytics, ML features, and downstream services.
  • Drive CI/CD for data code , infrastructure as code (Terraform or AWS CDK), and automated deployments.
  • Participate in architectural reviews, propose improvements for reliability, scalability, and cost; produce clear documentation and runbooks.
  • Mentor engineers, conduct code/design reviews, and promote engineering standards.
  • Mentor engineers, conduct code/design reviews, and promote engineering standards.

Carry out critical tech solutions across multiple technical areas as an integral part of an agile team