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 Senior 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 tasksMakes strategic decisions that influence teams’ resources, budget, tactical operations, and implementation of processes and proceduresEnsures successful collaboration across teams and stakeholdersIdentifies and mitigates issues to execute a book of work while escalating issues as necessaryProvides input to leadership regarding budget, approach, and technical considerations to improve operational efficiencies and functionality for the teamCreates 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.