Are you a visionary and execution-obsessed leader with a passion for delivering transformation? As the VPII of the Data Analytics Engineering, you will lead a team of data professionals to drive the strategic vision and execution of data initiatives across the organization. This role will simultaneously live in operational and strategic worlds. The VPII will work closely with business leaders, technology teams, legal, and compliance to embed data governance and architecture principles into core operations and foster a culture of accountability and innovation.
The VPII, Data Analytics Engineering is a transformative leader responsible for shaping and executing the enterprise’s data strategy to unlock business value and competitive advantage. S/he will lead the drive to improve data operations, operationalize a comprehensive data governance framework, implement enterprise data engineering best practices, and establish the organizational structures, standards, and processes necessary to ensure data quality, compliance, and ethical use for consumption by downstream reporting, AI, ML and data extracts.

REQUIREMENTS:

• Experience: 15+ years of experience in data engineering, architecture, governance and advanced analytics consumption, with at least 5 years in a senior leadership role.
• Execution: Proven track record of leading large-scale data enterprise data transformation programs with clearly articulated results.
• Education: Bachelor’s degree in Data Science, Computer Science, or a related field; Master’s degree preferred.
• Skills: Exceptional and proven leadership capabilities, including development of advanced analytic engineering teams. Outstanding communication and stakeholder engagement skills, with the ability to influence at the C-suite and board levels.
• Technical Proficiency: Deep expertise in data engineering and automation, governance frameworks, data privacy, and data compliance standards. Experience leading advanced data and full stack engineering teams. Experience with technical implementation of data cataloging, data quality assurance, observability and metadata management tooling. Data product and data mesh/fabric architecture experience preferred. AWS, Snowflake, dbt and API gateway and development experience preferred.
• Leadership: Proven track record of establishing, developing and leading high-performing data engineering teams.
• Communication: Excellent communication and stakeholder management skills. Strong business acumen is needed, and direct experience with business customers is required.

• Leadership and Strategy: Develop and implement the overall data strategy, ensuring alignment with business objectives and driving data-driven decision-making across the organization. Establish a Center of Excellence to transform engineering and quality practices within the organization; drive behaviors and change through this Center to establish and ensure these practices become standard ways of working across our engineering teams in Data Analytics.
• Data Analytics Architecture and Strategy: Oversee the design and delivery of modern, scalable data architectures that support advanced analytics, AI, and digital transformation initiatives. Partner with Cybersecurity, Enterprise Architecture, Core Data, Quality Assurance, Infrastructure, CDO’s organization and other technology and product teams to expand world-class data analytics infrastructure and standards.
• Data Product Value Development and Delivery: Partner with warehousing teams to establish security-focused, quality assured data product and data contract engineering standards for the management and rapid expansion of data products for consumption by AI and ML modeling teams, downstream consumers and BI layers. Drive the development and evolution of the data product quantum (data product standard architecture for integration, security, observability and compliance) leveraging AWS services, Snowflake, dbt and other enterprise-approved tooling. Emphasize rapid prototyping and continuous process improvement to enhance data capabilities and drive innovation
• Data Solution Modernization: Lead a team of high-performing engineers and analysts to evaluate, resolve, decommission and/or modernize legacy data solutions and applications, applying industry best practices and automation to expedite transformation.
• Data Security, Compliance, and Governance: Integrate data security, compliance, and governance policies, architectures and best practices across data analytics solutions to ensure we exceed regulatory and organizational standards.
• Metadata Management: Establish and maintain robust metadata management automation solutions within the data analytics ecosystem; advancing upstream and downstream integration to enterprise tooling to ensure data quality and accessibility.
• AI-Ready Data Pipeline Engineering: Partner with the AI engineering team to ensure the establishment of automation for maintenance, integration and CICD standards for AI-ready data pipelines to support advanced analytics and machine learning initiatives. Partner with API and AI gateway teams to ensure all data product solutions are fully integrated.
• Knowledge Graph Development and Delivery: Oversee the development and delivery of knowledge graphs engineering delivery to enhance data connectivity and insights, in partnership with product partners from the Chief Data Officer’s organization.
• Data Portal Development: Ensure full integration of the semantic layer to facilitate easier data querying and analysis. Develop a data portal to enable users (fellow engineers, data scientists and data analysts) to query and access data products with clear business meaning, value and quality standards through full integration with semantic and knowledge graph solutions.
• Strategic Planning: Conduct regular strategic planning sessions to align data initiatives with business goals. Work closely with cross-functional teams, including technology, product, President’s org to ensure data initiatives support business goals.
• Team Development: Develop a high-performing team of data engineers and analysts, fostering a culture of excellence and continuous learning. Develop career path opportunities and continuous learning opportunities for the team you will lead in partnership with SVP, Data Analytics and our HR business partner.
  What are we looking for? We’re looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates pursue greatness, act with integrity, and are driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we win together and create and share joy in our work.
  This is a highly impactful role, requiring collaboration and engagement with stakeholders to understand their data needs and ensure data solutions meet their requirements via data analytic infrastructure.