When you mentor and advise multiple technical teams and move financial technologies forward, it’s a big challenge with big impact. You were made for this.

As a Senior Lead Software Engineer of Software Engineering at JPMorganChase within the Consumer and Community Banking Technology Team, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm.

Job responsibilities

• Lead a high‑performing engineering team building and operating cloud‑native data platforms that ingest, process, and serve large‑scale batch and streaming data.
• Own end‑to‑end delivery for data warehousing and multi‑terabyte to petabyte‑scale migration initiatives, ensuring reliability, performance, security, and cost efficiency.
• Provide technical leadership across Java, Python, Spark, Snowflake, and AWS, while driving strong Agile practice, CI/CD automation, and operational excellence.
• Foster a culture of ownership, collaboration, psychological safety, and continuous learning.
• Own multi‑workstream roadmaps; plan releases, define milestones, track progress, and remove blockers to hit scope, schedule, and quality targets.
• Create detailed estimates and work breakdown structures, manage dependencies, risks, and stakeholder expectations.
• Define and evolve data platform architecture for batch and streaming use cases (event‑driven, microservices, warehouse patterns).
• Lead large‑scale data migration (on‑prem to cloud), data profiling, reconciliation, lineage, quality (e.g., deduplication, schema validation), and backfills.
• Define SLAs; implement monitoring/alerting; lead incident response, root cause analysis, and continuous improvement.
• Contribute to team culture of diversity, opportunity, and respect.

Required qualifications, capabilities, and skills

• Hands-on practical experience in system design, application development, testing and operational stability and CI-CD process.
• Hands-on practical experience in developing spark-based Frameworks for end-to-end ETL, ELT & reporting solutions using key components like Spark Core & Spark Streaming.
• Proficient in coding in one or more Coding languages – Java or Python
• Experience building Data Warehouse platform.
• Cloud implementation experience with AWS including:
  • AWS Data Services: Proficiency in Lake formation, Glue ETL (or) EMR, S3, Glue Catalog, Athena, Airflow (or) Lambda + Step Functions + Event Bridge
  • Data De/Serialization: Expertise in at least 2 of the formats: Parquet, Iceberg, AVRO, JSON
  • AWS Data Security: Good Understanding of security concepts such as: Lake formation, IAM, Service roles, Encryption, KMS, Secrets Manager
• Experience in Snowflake and Databricks.
• Experience in Gen AI skills.

Preferred qualifications, capabilities, and skills

• Experience working at code level
• In-depth knowledge of the financial services industry and their IT systems. Practical cloud native experience preferably AWS.

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Serve in a leadership role by providing technical coaching and advisory for multiple technical teams