JOB DESCRIPTIONWe 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 firmâs 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.
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