Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

• As a Senior 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 will drive significant business impact through your capabilities and contributions and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.

Job responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure high-quality production code, and reviews and debugs code written by others
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• 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
• 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 Py Spark/SparkSQL (Data Frame 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
• Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Ability to tackle design and functionality problems independently with little to no oversight
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• 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 Fin Ops 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.