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 the Finance Technology team which is aligned to Corporate Technology division , 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, opportunity, inclusion, and respect for team members and prioritizes diverse representation

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, 2 + years of experience leading technologists to manage and solve complex technical items within your domain of expertise
• Deeply passionate about learning and innovating using the latest and greatest in cloud, big data engineering and open source.
• Relevant experience in big data environment, working with structured, semi-structured and unstructured data
• Experience working at code level and provide oversight to the work done by the team members.
• Sound understanding of various data solution patterns and when to use them: ETL/ELT, RDBMS, Data modeling, Key-value, in-memory, streaming, messaging
• Strong software engineering and OOP skills with expertise in Python, Py Spark, Java , Airflow and Databricks, AWS, microservices architecture, cloud-native development
• Strong data architecture, data warehousing, data modeling and data manipulation skills such as in SQL, MySQL, Oracle, Postgres SQL and No SQL databases.
• Experience designing and implementing data solutions on AWS using offerings such as S3, Lambda, ECS, Aurora, Databricks/Snowflake.
• Strong attention to detail and ability to manage multiple projects and stakeholders
• Ability to produce quality results in evolving and fast-paced environment
• Strong communication skills (written and verbal), including ability to formulate and deliver engaging presentations that influence audience

Preferred qualifications, capabilities, and skills

• Experience building webservices, Data Products in Data Mesh
• Experience with containers, Kubernetes, ECS and Devop practices
• Experience building AI/ML solutions.