JPMorganChase
This role involves leading architecture and delivery of high-throughput, low-latency data pipelines using Databricks and Apache Spark within an agile team at a leading financial institution. The position requires establishing lakehouse patterns, driving the adoption of AI-assisted engineering practices, and optimizing Spark performance to ensure secure, stable, and scalable technology products. As a core technical contributor, you will oversee Databricks cluster strategy, orchestrate jobs, and design secure data ingestion frameworks leveraging AWS services. The role also includes enforcing data quality and governance, building reusable libraries, and implementing CI/CD for data projects.
JPMorgan Chase is a leading global financial services firm that provides a full range of banking, investment banking, asset and wealth management, and payments and treasury services to consumers, businesses, governments, and institutions. Its consumer business operates under the Chase brand, offering retail banking, credit cards, mortgages and auto loans, while J.P. Morgan delivers corporate & investment banking, markets, securities services and asset management. Headquartered in New York, the firm combines scale, technology and risk management to serve clients worldwide. It is one of the largest banks by assets and is widely recognized for its capital markets expertise and integrated financial solutions.
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
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JPMorganChase didn’t post a salary, so this is our estimate from similar listings.
5% above the average for this role