Director of Data Engineering - ServiceNow Configuration Management at JPMorganChase in BOURNEMOUTH

Job description

Be at the heart of building trusted, scalable data foundations that power critical technology and operational processes. Shape enterprise data architecture, pipeline patterns, and configuration management database outcomes in a resilient, controlled environment. Join a team where your leadership and partnership across product and engineering drives durable platforms and long-term career growth. As a Director of Data Engineering at JPMorganChase within Enterprise Technology’s unit, you will lead the enterprise CMDB strategy and data quality program to ensure trusted data foundations for operational and technology processes. As the enterprise data leader, you will define scalable data architecture, integration patterns, and pipelines; own CMDB governance and quality outcomes; and partner across product and engineering to deliver resilient, controlled platforms. This role leads ServiceNow configuration management database (CMDB) and related configuration/data domains, establishing scalable integration and data consumption patterns that support horizontal scale and performance as data volumes grow. You will work closely with product, architecture, engineering, infrastructure, cybersecurity, and data teams to drive shared outcomes—balancing delivery velocity with resilience, security, and control obligations through practical standards and measurable quality metrics. You will also enable safe, auditable use of enterprise‑approved AI, incorporating human‑in‑the‑loop validation where required. Job Responsibilities Define and drive the strategic direction for data engineering capabilities, including scalable data architectures, pipelines, integration, and data consumption patterns across a large-scale enterprise platform. Own configuration management database strategy and engineering, driving data quality, completeness, and integrity through scalable integration patterns so it remains a trusted foundation for operational and technology processes. Drive data strategies that enable horizontal scale, improved performance, and increasing data volumes while reducing technology, operational, and architectural risk. Establish and champion data standards across the software development life cycle, automated testing, observability, resilience, maintainability, and production readiness, ensuring security, data management, and control requirements are met. Deliver data pipeline and architecture solutions that can be leveraged across multiple businesses and domains through reuse-first patterns. Provides technology leadership for CMDB strategy and engineering, driving data quality, completeness, integrity and scalable integration patterns to ensure the CMDB remains a trusted foundation for operational and technology processes. Develop data talent and leadership capability while building strong partnerships across product, architecture, engineering, infrastructure, cyber security, and data organizations to deliver shared outcomes. Lead reuse-first adoption of enterprise-authorized artificial intelligence capabilities within the work environment to accelerate pipeline and architecture decisioning and delivery, with human validation and appropriate handling of sensitive data. Establish governance standards for artificial-intelligence-assisted workflows used in data engineering decision-making and delivery, ensuring traceability, auditability, and alignment to resilience, security, and control obligations. Influence peer leaders and senior stakeholders across business, product, and data technology teams to align priorities and execution. Required qualifications, capabilities, and skills Experience leading enterprise-scale data architecture and engineering, or similarly complex technology capabilities. Experience implementing data governance, data quality, and data management capabilities. Experience with modern data architecture and engineering patterns, including data pipelines, application programming interfaces, event-driven integration, data lakes