JPMorgan Chase is looking to evolve its data management, architecture, and analytics best practices within the Commercial & Investment Bank Credit Risk Data Enablement Team. The goal is to drive a shift to a data mesh architecture, support advanced AI/ML initiatives, and steer enterprise-wide data programs while ensuring compliance, operational excellence, and strategic innovation across data products.
Requirements
- Minimum 3+ years of progressive experience in data architecture, data engineering, technology consulting, or product management.
- Proven expertise in data integration, ETL development, and data mesh architecture within global financial environments.
- Strong technical proficiency in SQL, Python, and modern data visualization tools (e.g., Qlik, Tableau, or Power BI), with hands-on experience using cloud platforms (DataBricks, Snowflake, AWS Redshift).
- Demonstrated mastery in enterprise data management—including data lifecycle, metadata, and lineage practices.
- Solid experience with data modeling (conceptual, logical, and physical) and familiarity with architecture frameworks.
- Experience with advanced analytical tools (e.g., Python, Alteryx)
- Prior exposure to financial institutions and regulatory reporting requirements.
Responsibilities
- Drive the migration and integration of our cloud data infrastructure into a modern data mesh framework, collaborating with internal partners to document data integrations, SLAs, and data dictionaries (e.g., using Databricks Unity Catalog).
- Apply a deep understanding of data lifecycle management, metadata management, and data lineage to help execute on end-to-end enterprise data governance.
- Design ETL pipelines to automate the extraction, integration, and federation of data, complete with automated validation to maintain high data accuracy
- Work with data scientists leveraging machine learning and Gen AI techniques to deliver predictive analytics, anomaly detection, and actionable business insights.
- Collaborate on developing data models that promote data-driven decision-making across Risk, Banking, and Finance functions.
- Guide the development of conceptual, logical, and physical data models to ensure alignment with enterprise data strategies.
- Oversee enterprise-level data initiatives through robust program management, managing requirements and development timelines as part of digital transformation efforts.
Other
- Act as a liaison with partners, fostering relationships that drive continuous improvement and platform innovation.
- Help steer agile projects from conception through execution, ensuring seamless transitions and lasting improvements.
- Champion new data-driven initiatives and demonstrate adaptability, critical thinking, and strategic vision in rapidly evolving business environments.
- Excellent project and portfolio management skills, with a track record of engaging in transformation initiatives.
- Exceptional communication skills, effective in translating complex technical concepts for diverse, global audiences.
