Lead Software Engineer - Python and AWS Developer

Lead Software Engineer - Python AWS Developer

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 JPMorgan Chase in the Fusion Technology team, you design and deliver secure, scalable, and reliable software and data services that power critical products for our customers and partners.

Job responsibilities

• Design, build, and operate robust Python services and RESTful APIs using frameworks such as FastAPI or Flask, with clear contracts, validation, versioning, and secure-by-default patterns.
• Develop scalable ETL and batch data pipelines with PySpark on platforms like EMR or Databricks, optimizing transformations, joins, partitioning, and Spark SQL for performance.
• Model and query relational data with strong SQL; contribute to schema design, indexing strategies, and safe, controlled migrations that support reliability and growth.
• Integrate AWS services from application code using SDKs (e.g., S3, Secrets Manager, DynamoDB, Aurora), applying least-privilege IAM and resilient patterns for fault tolerance.
• Write high-quality production code and tests (unit, integration, contract) with pytest, type hints, and linters; review and debug code authored by others to maintain quality and consistency.
• Diagnose and resolve issues using structured logging, metrics, and profiling; perform root-cause analysis and implement resilient error handling, retries, and backoff strategies.
• Lead evaluation and adoption of new technologies; mentor peers and junior engineers, contribute to communities of practice, and help evolve standards for secure coding, observability, and performance.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Proficiency in Python for services and data engineering, including FastAPI or Flask, async fundamentals, and testing with pytest; strong SQL and data modeling skills.
• Hands-on PySpark experience for distributed data processing on cloud platforms such as EMR or Databricks, including Spark SQL and performance-aware transformations.
• Practical AWS development experience using boto3 and core services (e.g., S3, Secrets Manager, DynamoDB or Aurora) with application-level IAM and least-privilege access.
• Demonstrated ability to design and deliver secure, production-grade code; advanced debugging, performance tuning, and robust API design.
• Proficiency across the Software Development Life Cycle and modern engineering practices, including CI/CD, application resiliency, and secure coding.
• Effective communication and mentorship skills with a track record of collaboration across teams to deliver stable, observable, and maintainable systems.

Preferred qualifications, capabilities, and skills

• Advanced Python performance techniques such as profiling at scale and integration with Rust for compute-intensive workloads.
• Advanced data engineering with Spark, including Structured Streaming, Delta Lake or Apache Iceberg, and data quality frameworks such as Great Expectations.
• Application security and reliability depth, including OAuth2 or OIDC integration, scalable concurrency patterns, and property-based or fuzz testing methods.
• Experience leading outcomes-oriented technical evaluations with external vendors or internal platforms and shaping architecture within complex environments.
• Practical cloud-native design patterns and familiarity with both relational and NoSQL data stores in high-availability, compliance-focused settings.