Vice President, Firmwide Resiliency Office Data Management Lead

The Firmwide Resiliency Office (FRO), part of the Office of the Chief Finance Officer, is responsible for designing the Firm's Resilience strategy. This includes Resiliency Planning, Testing, Exercising, Reporting, and Product and Concern Management. The team comprises technical product, data, and analytic roles that support business resiliency. FRO collaborates closely with senior leadership, Lines of Business, Functional Resiliency teams, and key functions such as Control Management, Risk Management & Compliance, and Audit to ensure the resiliency program aligns with the firm's risk-taking activities. Additionally, the team provides corporate governance, awareness, and training.

As a Data Management Vice President within FRO, you will play a crucial role in supporting data strategies for the Firm's Resilience Program. You will work closely with all areas of FRO and key stakeholders across Lines-of-Business (LOBs) and Corporate Functions (CFs). This role requires an execution-oriented approach, exceptional data analytical skills, and full engagement with the overall program. A key responsibility will be implementing initiatives to enhance and automate resiliency data management frameworks. You will design and implement data strategies, facilitate data sharing, and establish data governance and controls using advanced data wrangling and business intelligence tools. Your expertise in SQL, Python, data transformation tools, and experience with AI/ML technologies will be essential in driving these initiatives forward.

Job Responsibilities:  

• Design, develop, and maintain scalable data pipelines and ETL processes using Databricks and Python and write complex SQL queries for data extraction, transformation, and loading.
• Develop and optimize data models to support analytical needs and improve query performance and collaborate with data scientists and analysts to support advanced analytics and AI/ML initiatives
• Automate data processes and reporting using scripting utilities like Python, R, etc.
• Perform in-depth data analysis to identify trends and anomalies, translating findings into reports and visualizations.
• Collaborate with stakeholders to understand data requirements and deliver data services promptly.
• Partner with data providers to design data-sharing solutions within a data mesh concept.
• Oversee data ingestion, storage, and analysis, and create rules for data sharing and maintain data quality and integrity through automated checks and testing
• Monitor and analyze data systems to enhance performance and evaluate new technologies and partner with technology teams and data providers to address data-related issues and maintain projects.
• Contribute to the design and implementation of data governance frameworks and manage firm-wide resiliency data management frameworks, procedures, and training.
• Stay updated with emerging data technologies and best practices and develop and maintain documentation for data engineering processes.
• Lead and manage a team of data professionals, providing guidance, mentorship, and performance evaluations to ensure successful project delivery and professional growth.

Required qualifications, skills and capabilities:

• Bachelor's degree in computer science, Data Science, Statistics, or a related field, or equivalent experience.
• Expert in SQL for data manipulation, querying, and optimization, with advanced database experience.
• Proficient in scripting utilities like Python, R, etc.; including data analysis libraries such as Pandas and NumPy.
• Proficient in data transformation tools like Alteryx, and Tableau, and experienced in working with APIs.
• Direct experience with Databricks, Spark, and Delta Lake for data processing and analytics.
• Experience in data reconciliation, data lineage, and familiarity with data management and reference data concepts.
• Excellent analytical, problem-solving, and communication skills, with a collaborative and team-oriented mindset.
• Solid knowledge of software architecture principles, cloud-native design (e.g., AWS, Azure, GCP), containerization (Docker, Kubernetes), and CI/CD best practices.
• Self-starter with strong verbal, written, and listening skills, and excellent presentation abilities.
• Proven influencing skills and the ability to be effective in a matrix environment.
• Understanding of operational resilience or business continuity frameworks in regulated industries 
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Preferred qualifications, skills and capabilities:

• 10 + years of experience in data management roles such as Data Analyst or Data Engineer.
• Strong understanding of data warehousing concepts and principles.
• Skilled in handling large, complex datasets for advanced data analysis, data mining, and anomaly detection.
• Experience with AI/ML technologies and frameworks