Lead Software Engineer - Platform Engineering Databricks

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The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

As a Lead Software Engineer at JPMorgan

Chase within the Chief Data Analytics Office - AIML Data Platforms Team, 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.

• 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

• Solves the companies' most challenging cloud data platform problems by building innovative technical solutions around Data Lake Tools.

• Designs, implements, and maintains a managed Apache Spark on Kubernetes, AWS Databricks platform, and provides engineering and operational support for the platform to SRE and app teams.

• Performs platform design, set‑up and configuration, workspace administration, resource monitoring, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams.

• 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 opportunity, inclusion, and respect

• Formal training or certification on software engineering concepts and 5+ years applied experience

• Hands‑on experience with Python and/or Java application program development with use of automated unit testing

• Hands‑on experience in Big Data Compute Engines Apache Spark - Core, SQL (Catalyst Framework), Databricks platform, Kubernetes platform

• Experience in designing, developing, or maintaining production‑grade cloud solutions in Cloud ecosystems such as Amazon Web Services (VPC, EKS, EFS)

• Hands‑on practical experience delivering system design, application development, testing, and operational stability. Ability to tackle design and functionality problems independently with little to no oversight

• Hands‑on experience with Git Hub / Bitbucket SCM, Jenkins, CI/CD tool, Docker, building container image, Terraform and pypi / maven artifactory integrations

• Exposure to AWS & Databricks Platform administration
• Experience with Agile development processes, as needed (SCRUM/KANBAN) using JIRA.
• Experience in Data pipelines using Spark
• Experience in managing product release lifecycle at enterprise level.