Lead Software Engineer - Data

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 - Data at JPMorgan Chase within the Corporate Sector - Cloud Financial Management Technology group, 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 5+ years applied experience
• Proficiency in Python for data engineering and advanced PySpark/SparkSQL (DataFrame APIs, UDFs/pandas UDFs)
• Spark performance/tuning skills: partitioning, shuffle minimization, broadcast joins, AQE, skew handling, caching, and reliable backfills
• S3 data lake design and security: bucket/partition layout, lifecycle/versioning, SSE-KMS encryption, cross-account access, and Lake Formation/IAM
• Experience with open table formats and lakehouse patterns (e.g., Apache Iceberg, Delta Lake, Apache Hudi): table design/evolution, partitioning, snapshot/time‑travel concepts, and cross‑engine interoperability
• Experience with distributed columnar data warehouses (e.g., Redshift, BigQuery, Snowflake): dimensional modeling, performance tuning, bulk load/unload
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficient in all aspects of the Software Development Life Cycle
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• In-depth knowledge of the financial services industry and their IT systems
  

Preferred qualifications, capabilities, and skills

• Ability to translate business requirements into data models, contracts, SLAs, and measurable outcomes with clear business impact.
• Knowledge of FinOps practices: budget/tagging discipline, right-sizing and autoscaling, storage/query cost optimization, and cost-aware design trade‑offs.
• Experience implementing data quality and reliability guardrails aligned to business SLAs (freshness, completeness, accuracy) with actionable alerting.
• DevOps/IaC for data: CI/CD for Spark/Glue jobs, Terraform/CloudFormation/CDK, git-based versioning, and blue/green or canary publishes.
• Experience building and operating AWS Glue 3.x/4.x ETL jobs and orchestrating via Step Functions or Glue Workflows.