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 Python Senior Manager of Software Engineering at JPMorgan Chase within the Firmwide Planning and Analysis Data Platform Team, you serve in a leadership role by providing technical coaching and advisory for multiple technical teams, as well as anticipate the needs and potential dependencies of other functions within the firm. As an expert in your field, your insights influence budget and technical considerations to advance operational efficiencies and functionalities.

Job responsibilities

Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks 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 Creates a culture of diversity, equity, inclusion, and respect for team members and prioritizes diverse representation

Required qualifications, capabilities, and skills

Formal training or certification on software engineering concepts and  advanced applied experience in Data Management, Data Integration, Data Quality, Data Monitoring  and Analytics experience. Experience leading teams of technologists  and managing global stakeholders Experience in data engineering with proficiency in Python and PySpark.   Experience with building Cloud native applications using cloud platforms such as AWS, Azure, GCP and experience in leveraging cloud services for data storage, processing and analytics. Hands-on experience in data integration and handling projects that involves processing huge volume of data for reporting models.  Hands-on experience in database system (both SQL and NOSQL) and create/maintain scalable database load process with framing up Complex SQL Queries and ensuring optimal data storage and retrieval. Expertise in working with agile projects to automated testing / dev ops environments. Knowledge of big data technologies such Apache Spark or Pyspark Hands-on experience with containerization technologies like Docker and Kubernetes (EKS). Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives