Lead Software Engineer - Data

Description

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 at JPMorganChase within the Corporate Technology team, you will design, develop, and deliver scalable, consumer-aligned data products that power executive reporting , analytics, AI and business applications.

This role is ideal for an experienced software engineer who has a deep expertise in data development and is passionate about transforming complex enterprise data into trusted reusable products.

The ideal candidate has extensive experience with Databricks, SQL, PySpark, Oracle and modern data engineering practices.

They will partner with the business stake holders, analytics teams, UI developers, and product owners to build high quality data products that enable self-service analytics, dashboards, AI solutions, and operational reporting.

Job Responsibilities


* Design, develop, and maintain consumer-aligned data products that support enterprise reporting analytics


* Develop curated datasets (Delta Lake tables) and analytics-ready models to support reporting, dashboards, and decision-making.


* Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.


* Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.


* Design efficient, maintainable SQL queries, views, stored procedures, and reusable data models


* Build reusable data assets that support dashboards, AI use cases, automation, and business applications


* Ensure data quality, governance, lineage, and documentation are incorporated into all solutions


* Optimize data processing performance and identify opportunity to improve scalability and efficiency


* Collaborate closely with frontend developers, analytics engineers, UX Designers and product owners


* Stay current on emerging technologies and recommend improvements in cloud data architecture , AI, and automation

Required Qualifications, Capabilities, and Skills


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


* 8+ years in software engineering and/or data application development.


* Expert-level SQL development experience, including query tuning and performance optimization.


* Extensive experience with Databricks and the Databricks Lakehouse Platform.


* Strong experience building data applications and pipelines using PySpark.
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