Manager of Software Engineering - Data Engineering Expertise

You have the opportunity to unleash your full potential at a world-renowned company and take the lead in shaping the future of technology.

As a Manager of Data Engineering at JPMorgan Chase within the Consumer & Community Banking, 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 data users 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
• Makes strategic decisions that influence teams’ resources, budget, tactical operations, 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 data engineering concepts and 5+ years applied experience.
• Demonstrated coaching and mentoring experience.
• Hands-on experience in writing code using Python libraries such as Pandas, Boto3, PySpark, and Jupyter Notebooks, along with 3+ years of AWS services experience including Glue, Iceberg, S3, Kafka, and AWS.
• Hands-on practical experience delivering system design, application development, testing, and operational stability.
• Collaborate with various stakeholders and independently tackle design and functionality challenges with minimal oversight.
• Proficient in automation and continuous delivery methods.
• Skilled in resolving code issues and proficient in Git for managing repositories and team collaboration.
• Experience and proficiency across the data lifecycle.
• Evaluates and reports on access control processes to determine effectiveness of data asset security​ with minimal supervision.
• Advanced understanding of agile methodologies, Application Resiliency, and Security.
• Bachelor’s degree in data science, Computer Science, Information Systems, Statistics, or a related field.

Preferred qualifications, capabilities, and skills

• Strong Python experience, especially in the context of developing solutions for large financial platforms.
• Strong experience in AWS serverless services including expertise in using AWS Step functions, Lambda, and NoSQL database services
• Experience using AWS Lake Formation service.
• Familiarity with Snowflake/Databricks or other PaaS offerings.
• Experience with metadata management and machine learning.