Lead Software Engineer - Data

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.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans