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 - Data Engineering Lead at JPMorgan Chase within Commercial and Investment Bank Technology, you will be required to apply your depth of knowledge and expertise to all aspects of the software development lifecycle, as well as partner continuously with your many stakeholders on a daily basis to stay focused on common goals. You will work in a collaborative, trusting, thought-provoking environment-one that encourages diversity of thought and creative solutions that are in the best interests of our customers globally.

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
Ensure successful collaboration with Product and Business Partners
Gather and understand requirements, design and contribute to the architecture, create target state architecture and dataflows.
Acquire data from primary or secondary data sources, identify, analyze, and interpret trends or patterns in complex data sets
Transform existing ETL logic on AWS Platform or Data Bricks
Innovate new ways of managing, transforming and validating data, and apply quality assurance best practices to all work products
Implement new or enhance services/scripts, establish and enforce guidelines to ensure consistency, quality and completeness of data assets
Analyze, design and code business-related solutions, as well as core architectural changes, using an Agile programming approach resulting in software delivered on time and in budget
Sets and scales operating practices for enterprise-authorized AI-assisted engineering and SDLC/TLM automation across multiple teams to improve delivery speed, quality, and operational outcomes establishes measurable expectations (e.g., throughput, defect reduction, reliability) and ensures consistent validation, security, resiliency, and reuse of proven patterns.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to drive efficiency and support capacity unlock initiatives across teams, prioritizing reuse of existing firm technology assets.

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
Advanced knowledge of application, data and infrastructure architecture disciplines
Experience in a Big Data technologies (e.g. AWS, Spark, Kafka, Data Bricks etc.), along with experience in Java and Python
Experience in writing efficient SQL's and implementing complex ETL transformations on big data platform
Strong experience with UNIX shell scripting to automate file preparation and database loads, and familiarity with relational database environment (Oracle, SQL Server, etc.) leveraging databases, tables/views, stored procedures, agent jobs, etc.
Experience in data quality testing adept at writing test cases and scripts, presenting and resolving data issues
Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
Demonstrated independent problem solving skills and ability to develop solutions to complex analytical/data-driven problems, along with ability to communicate complex issues in a crisp and concise fashion to multiple levels of management
Excellent interpersonal skills necessary to work effectively with colleagues at various levels of the organization and across multiple locations with ability to manage multiple priorities and projects coupled with the flexibility to quickly adapt to ever-evolving business needs
Experience leading multi-team adoption of enterprise-authorized AI-assisted development and delivery tools, including defining governance/ways of working (human-in-the-loop validation, quality gates), measuring outcomes, and ensuring secure handling of sensitive inputs/outputs.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and control expectations ability to coach managers/leads and influence leaders on safe scaling patterns.
Preferred qualifications, capabilities, and skills
Experience of working in a development teams, using agile techniques and Object Oriented development and scripting languages, is preferred
Comfortable learning cutting edge technologies and applications to greenfield project
Experience in Data Science, Machine Learning and AI is a plus
Financial Services and Commercial banking experience is a plus
Familiarity with NoSQL platforms(MongoDB, AWS Open Search) is a plus
3+ years of experience with Python is preferred
2+ years of Experience in Java Development