Senior Manager of Software Engineering - Python , spark , data modelling

When you mentor and advise multiple technical teams and move financial technologies forward, it's a big challenge with big impact. You were made for this.

As a Senior Manager of Software Engineering at JPMorgan Chase within Corporate Technology, you will serve in a leadership role by offering technical coaching and advisory to multiple technical teams. Additionally, you will anticipate the needs and potential dependencies of other functions within the firm.

Job responsibilities

• Provides overall direction, oversight and coaching for a team of entry-level to mid-level data engineers that work on basic to moderately complex tasks
• Work with business and technology product owner on Product backlog prioritization
• Be accountable for decisions that influence teams' resources, budget, tactical operations, and the execution and implementation of processes and procedures
• Ensures successful collaboration across teams and stakeholders
• Identifies and mitigates issues to execute a book of work while escalating issues as necessary
• Provides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the team

• Formal training or certification on software engineering concepts and 7+ years applied experience
• Extensive 10 +experience in managing the full lifecycle of data, from collection and storage to analysis and reporting.
• Proficiency in one or more large-scale data processing distributions such as PySpark along with knowledge on Data Pipeline (DPL), Data Modeling, Data warehouse, Data Migration and so-on
• Strong SQL skills for querying and managing relational databases
• Proficient in coding in one or more modern programming languages
• Should have good hands-on experience on AWS services and its components along with good understanding on Kubernetes.
• Experience leading teams of technologists
• Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives
• Experience with hiring, developing, and recognizing talent
• Practical cloud native experience
• Experience in Computer Science, Engineering, Mathematics, or a related field and expertise in technology disciplines

• Experience of Databricks or similar lakehouse technologies
• Experience in building AI solutions on Data Lake