Lead Software Engineer (Databricks)

At JPMorgan Chase, you’ll join a team that values diverse perspectives and encourages bold thinking. We foster a supportive, blame-free environment where you can take risks, learn, and grow. You’ll have the autonomy to work on meaningful projects while receiving mentorship and support. We’re excited to see how your unique background and ideas will help shape our future together.
As a Manager of Software Engineering at JPMorgan Chase as a part of Employee Platforms, you will lead and inspire a group of talented engineers to deliver secure, stable, and scalable technology solutions. You will play a key role in designing, developing, and troubleshooting software components that drive our state-of-the-art products. You’ll collaborate with cross-functional teams and help shape the technical direction of our projects. Your leadership will empower your team to innovate and excel.
Job Responsibilities:
Manage data integration and analysis across diverse systems
Build extensible data acquisition and integration solutions to meet client requirements
Implement processes to extract, transform, and distribute data from various sources
Provide expertise in problem-solving and complex data analysis for business intelligence integration
Collaborate with internal product development and cross-functional teams
Work with remote and geographically distributed teams to deliver consumable products
Required Qualifications, Capabilities, and Skills:
Experience in data integration projects using Big Data technologies, preferably in human resources analytics
Proven ability to manage engineering teams
Hands-on experience with AWS Data Warehousing and database platforms (Databricks preferred), including EMR, S3, AWS Glue, Lambda, Apache Airflow, and Infrastructure as Code tools (e.g., Terraform, CloudFormation)
Proficiency in Spark engineering with PySpark or Scala for scalable data pipelines
Experience building streaming applications using Kafka
Strong background in CI/CD using Jenkins, Git, Artifactory, YAML, and Maven for cloud deployments
Knowledge of Big Data querying tools such as Athena, RDS, and Databricks
Experience integrating data from various file-storage formats (Parquet, ORC, Avro) and table formats (Delta Lake, Iceberg)
Familiarity with Java open-source tools, API standards, JUnit, Spring Boot, and Swagger
Experience using AI-assisted developer productivity tools (e.g., GitHub Copilot)
Technical expertise in building scalable, high-performance distributed systems
Knowledge of Data Warehousing, Data Modeling, Data Lake, and Data Security concepts
Strong problem-solving, troubleshooting, and analytical skills
Excellent communication, presentation, and interpersonal skills
Experience with Oracle/SQL and NoSQL data stores such as DynamoDB
Ability to quickly learn new technologies in a dynamic environment
Preferred Qualifications, Capabilities, and Skills:
Experience leading data integration projects in large, complex organizations
Advanced knowledge of cloud-based data solutions
Familiarity with emerging technologies in data engineering and analytics
Demonstrated ability to mentor and develop engineering talent
Experience working in agile development environments
Strong track record of delivering innovative solutions
Commitment to fostering an inclusive and collaborative team culture