JOB DESCRIPTION Your opportunity to make a real impact and shape the future of financial services is waiting for you Lets push the boundaries of whats possible together As a Data Governance Engineering Lead at JPMorgan Chase in the Chief Data Analytics Office you will lead complex multifunctional technology projects and programs that will impact experiences for multiple groups across the firm including clients employees and stakeholders With your advanced analytical reasoning and adaptability skills will enable you to break down business technical and operational objectives into manageable tasks while navigating through ambiguity and driving change With demonstrated technical fluency you will effectively manage resources budgets and crossfunctional teams to deliver innovative solutions that align with the firms strategic goals Your exceptional communication and influencing abilities will foster productive relationships with stakeholders ensuring alignment and effective risk management In this pivotal role you will contribute to the development of new policies and processes shaping the future of our technology landscape Job responsibilities Manage the Data Governance roadmap across the organization ensuring alignment with evolving global privacy strategic priorities and lines of business Lead key Firmwide privacycentric initiatives such as consent management data retention crossborder data transfer governance Responsible for the structure of roadmap delivery and operating model across the organization Oversee engineering projects risks issues and dependencies across the Data Governance book of work Develop and maintain data governance metrics KPIs and dashboards to provide executivelevel visibility into the firms privacy posture incident trends and regulatory compliance status Prepare and deliver comprehensive reports and presentations to CLevel Executives including the Operating Committee to communicate program status risks and achievements Partner with the product organization to drive business outcomes ensuring that technical programs are aligned with strategic business goals Sets and scales multidepartment strategy for agentic AIenabled engineering and SDLC TLM automation using enterpriseauthorized tools within the work environment to drive firmwide objectives speed scalability reliability and costtoserve including portfoliolevel standards for AIorchestrated delivery workflows release governance automated test modernization resilience engineering and incident response acceleration establishes guardrails for validation security resiliency traceability and reuse Applies knowledge of tools within the Software Development Life Cycle toolchain including enterpriseauthorized AIassisted development and automation capabilities to drive crossdomain reuse and measurable capacity unlock outcomes across departments Required qualifications capabilities and skills 10 years of leadership in building technology applications and architecture with an overall of around 20 years experience and 5 years at Director level Strong understanding of global data governance regulations to drive technical architecture decisions and engineering requirements Strong experience in program management stakeholder management and building technical data platforms using AWS Experience with enterprisescale implementations of cloudnative data platforms such as Databricks and Snowflake Experience navigating complex data governance security and compliance requirements across multicloud and hybrid data environments at enterprise scale with demonstrated proficiency in technical solutions vendor product knowledge managing vendor relations and implementing solutions Knowledge of records retention legal holds and defensible disposal across structured and unstructured data including backups and snapshots Proven track record deploying and governing enterprise metadata catalog and lineage platforms plus practical expertise with data contracts and schema governance Demonstrated ability to evaluate and drive technical decisions regarding data platform tradeoffs including performance optimization cost management scalability and operational excellence Technical understanding of modern data platform architectures including data lakes data warehouses lake house architectures and distributed computing frameworks Experience leading multiorganization adoption of agentic AIenabled engineering operating models using enterpriseauthorized tools within the work workplace including defining governance humanintheloop decisioning quality gates measurement frameworks and secure handling of sensitive inputs outputs across teams Deep understanding of responsible AI risk controls and resiliency security expectations at scale with demonstrated ability to advise senior leaders on safe adoption portfolio governance and reusefirst

📌 Senior Director of Software Engineering Data Governance Program Management (Hyderabad)
🏢 JPMorganChase
📍 Hyderabad