Lead Software Engineer - Python/PySpark/Databricks/AWS

JPMorgan Chase & Co.
Delaware, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Delaware, United States of America

Tech stack

Agile Methodologies
Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Software Applications
Automation of Tests
Software Quality
Code Review
Continuous Integration
Data Validation
Identity and Access Management
Python
Key Management
Metadata
Modular Design
Networking Basics
Performance Tuning
Software Tools
Secure Coding
Software Engineering
Software Systems
Data Streaming
Strategies of Testing
Toolchain
Data Logging
Data Processing
Spark
Caching
Amazon Web Services (AWS)
Data Lake
PySpark
Integration Tests
Production Code
Code Restructuring
Software Version Control
Databricks
Programming Languages

Job description

As a Lead Software Engineer - Python/PySpark/Databricks/AWS at JPMorganChase within the Corporate Technology team, 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., * 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
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.

Requirements

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Experience building and operating Databricks Lakehouse solutions hosted on Amazon Web Services (AWS), including Amazon S3, Identity and Access Management (IAM), Key Management Service (KMS), basic networking concepts (VPC/security groups), and logging/auditing.
  • Experience using Delta Lake (ACID-compliant tables, partitioning strategies, schema evolution) and Apache Spark on Databricks, including performance optimization (cluster sizing, skew mitigation, join strategies, caching, and file sizing/compaction).
  • Experience delivering batch and streaming data pipelines (Structured Streaming, incremental processing, backfills, late-arriving data handling) and implementing governance/security controls in Databricks (e.g., Unity Catalog, table/column-level permissions, credential passthrough where applicable), with operational ownership including monitoring/alerting, incident response, root-cause analysis (RCA), and service level objective/service level agreement (SLO/SLA) management.
  • Advanced in one or more programming language(s) including Python, PySpark
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Architect Databricks Lakehouse solutions, including bronze/silver/gold (or equivalent) layering and domain-oriented data products; implement resilient, scalable ingestion from AWS sources into Databricks using batch and streaming patterns (including CDC where required).
  • Build maintainable pipelines using Delta Live Tables (DLT) and/or Databricks Jobs/Workflows with modular design, documentation, and runbooks; ensure production readiness through retries, checkpointing, idempotency, safe re-runs, and defined replay/backfill procedures; implement testing practices including unit/integration tests, data quality checks, and contract testing; Apply governance-by-design controls (least privilege, PII classification, auditing, lineage/metadata, controlled sharing/consumption); optimize Spark/Delta performance and cost (cluster right-sizing, storage layout, job/warehouse spend); lead design/code reviews and mentor engineers; partner cross-functionally with stakeholders and security/platform teams; deliver CI/CD and infrastructure-as-code for Databricks + AWS with promotion across environments and strong version control/code review discipline.

Preferred qualifications, capabilities, and skills

  • AI experience

Benefits & conditions

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

About the company

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

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