Lead Software Engineer Python, Databricks, AWS

We have an opportunity to impact your career and provide an adventure where you can push the limits of whats possible. Join our innovative External Regulatory Financial Control (ERFC)/Strategic Data team at JPMorganChase where we leverage cutting-edge technology to drive data-driven decision-making and enhance business performance. We are seeking a talented and motivated Software/Data Engineer to join our team and contribute to our mission of transforming data into actionable insights.

As a Lead Software Engineer at JPMorgan Chase within the External Regulatory Financial Control (ERFC)/Strategic Data team you will play a crucial role in designing developing and maintaining scalable data processing solutions using Databricks Python and AWS. You will collaborate with cross-functional teams to deliver high-quality data solutions that support our business objectives.

Job responsibilities

• Execute creative data-driven software solutions including design development and technical troubleshooting with the ability to think beyond routine approaches to solve technical problems.
• Design develop and maintain scalable data pipelines and processing workflows using Python PySpark SQL and Databricks on AWS processing and transforming large-scale financial datasets for analytics and reporting.
• Develop fact and dimension data models for reporting and analytics.
• Write secure high-quality production code and review and debug code written by others.
• Ensure data quality consistency security and lineage throughout all stages of data processing and transformation implementing monitoring and alerting mechanisms to maintain pipeline reliability.
• Support data migration and modernization initiatives transitioning legacy systems to cloud-based data warehouses.
• Lead communities of practice across Software Engineering to promote awareness and adoption of new technologies. Foster a team culture of diversity opportunity inclusion and respect.
• Mentor and guide Associate-level engineers supporting their technical development and ensuring consistent delivery standards across the team.
• Collaborate with business stakeholders to develop data management strategies transforming data into insights that drive strategic decisions.
• Document data flows logic and transformation rules to maintain transparency and facilitate knowledge sharing.
• Lead and Participate in the full Software Development Life Cycle (SDLC) including requirements gathering design development testing deployment and maintenance
• Identify and automate remediation of recurring issues to improve operational stability acting as both Production Support and SRE function for data pipelines and platform services.
• Utilise AI tools to accelerate development and testing of data pipelines (e.g. GitHub CoPilot Claude Code).

Required qualifications capabilities and skills

• Proven experience in data management ETL/ELT pipeline development and large-scale data processing.

• Proficiency in SQL Python and PySpark with experience in query optimization and performance tuning.

• Hands-on experience with data lake platforms (Databricks Apache Spark or similar).

• Experience with AWS cloud services (S3 ECS SNS/SQS Lambda etc.).

• Strong understanding of data quality security and lineage best practices.

• Experience with cloud-based data warehouse migration and modernization.

• Proficient in CI/CD continuous delivery methods (Jules/Jenkins Spinnaker Sonar) the full Software Development Life Cycle and Agile methodologies.

• In-depth knowledge of the financial services industry and their IT systems.

• Excellent problem-solving troubleshooting and analytical skills with ability to investigate data issues identify root causes and implement solutions.

• Strong communication and documentation abilities with the ability to collaborate effectively with business and technical stakeholders.

Preferred qualifications capabilities and skills

• Knowledge of regulatory reporting and financial data aggregation techniques.
• Experience with data orchestration tools (Airflow Step Functions etc.).
• Databricks or AWS certifications.
• Demonstrated proficiency in cloud-native development (e.g. cloud artificial intelligence machine learning).
• Experience with Parquet JSON CSV Avro Delta Lake file formats.