Bring your expertise to JPMorganChase. As part of Risk Management and Compliance, you are at the center of keeping JPMorganChase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

As a Senior Data Engineer - Executive Director on the Core Platform team within Wholesale Credit Risk QR (Quantitative Research), you will spearhead the development and execution of advanced data architectures and strategies supporting the Wholesale Credit Risk domain, create systemic solutions to address data governance mandates and standardize data onboarding pipelines. You must possess technical expertise in distributed systems, big-data technologies and cloud-enabled solutions.

Job Responsibilities

Strategic Data Architecture Development

Design and implement on-premise and cloud-enabled data architectures for the ingestion, processing and storage of credit risk data Oversee the integration of structured and unstructured data sources, enabling predictive modeling and scenario analysis. Develop and enforce best practices for data lakehouse designs and distributed compute platforms like Apache Spark and Databricks

Governance and Compliance

Ensure data systems meet regulatory requirements such as Basel III, IFRS9 and CCAR, while maintaining high standards of security and governance Establish robust data governance frameworks, focusing on quality, consistency and operational excellence Establish tooling to ensure full data lineage visibility and reporting

Leadership and Stakeholder Engagement

Partner with senior risk and business leaders to identify opportunities for leveraging data to inform decision-making Mentor and upskill teams in advanced data technologies, fostering a culture of innovation and continuous learning

Required qualifications, capabilities and skills

10+ years in data engineering, architecture or analytics roles with a strong focus on banking and financial services Proficiency in distributed computing technologies (eg Apache Spark, Databricks), cloud platforms (AWS, Azure, GCP) and data-lake architectures Hands-on experience with tools like Hadoop, Delta Lake, Kubernetes, Snowflake and Kafka Strong programming skills in Python, Java and SQL with expertise in data pipeline development and ETL processes Proven ability to lead cross-functional teams and manage complex data initiatives Strong communication skills with the ability to bridge technical and business audiences Experience in stakeholder engagement, aligning technical strategies with organizational objectives

Preferred qualifications and experience

Knowledge of risk methodologies, Wholesale Credit, CCAR, Allowance (CECL/IFRS9), Basel II/III regulatory capital