Associate Vice President – Data Analytics

We are seeking a visionary yet deeply technical Associate Vice President – Data Analytics to lead the design, development, and evolution of enterprise data architecture with a particular emphasis on database engineering , data warehousing , and data integrity to enable corporate reporting and AI technology solutions . This role will drive scalable, secure, and integrated solutions that empower business leaders with actionable insights, enable AI-driven innovation, and ensure data consistency across platforms. The ideal candidate is a hands-on leader with deep expertise in data architecture and business insight tools, capable of setting strategic direction while also rolling up their sleeves to design systems and solve complex challenges. You will play a central role in unifying fragmented data ecosystems across payroll, CRM, and other business platforms (e.g., ClientSpace, Prism, iSolved, Snowflake, UDC, etc.), building a scalable foundation for enterprise analytics and automation in a rapidly growing environment. Key Responsibilities: Data Infrastructure Design and lead the development of a modern, scalable enterprise data architecture, including warehousing and integration strategy. Assess, implement, and optimize solutions like Snowflake, Azure SQL, UDC, or other custom database platforms as needed. Evaluate and implement strategies like read replicas, ETL pipelines, and API integrations to support reliable data access without disrupting source systems (e.g., ClientSpace). Develop and manage a data lake / warehouse strategy that supports AI readiness, predictive analytics, and automation. Data Integrity Oversee efforts to eliminate data silos, resolve ID mismatches (e.g., PEOID discrepancies), and ensure synchronization across platforms. Design and enforce best practices for data hygiene, validation, and mapping logic across the enterprise. Governance, Security & Compliance Establish standards for data governance, including access controls, data classification, confidentiality, and auditability. Ensure data solutions comply with internal security standards and any applicable legal or regulatory requirements. Partner with IT and Security to align infrastructure with data protection and cybersecurity protocols. Strategic Innovation and AI Enablement Build the data backbone required to enable advanced analytics, AI models, and process automation across departments. Support business units in evaluating and piloting AI/ML initiatives, ensuring data pipelines and platforms are aligned with future needs. Identify and recommend opportunities for tool commercialization to Prism clients. Cross-Functional Collaboration and Leadership Act as a strategic partner to leaders in Finance, HR, IT, Operations, and beyond to drive enterprise-wide data solutions. Serve as a Center of Excellence (CoE) for best practices in database engineering, analytics, and data architecture. Provide technical mentorship and guidance to data engineers, analysts, and cross-functional teams. Vendor & Tool Evaluation Evaluate and recommend third-party tools, platforms, and services related to data warehousing, BI, and integration. Complete alternative identification, cost-benefits analyses, gap analyses, and RFPs as needed related to third-party data services and technology. Lead or participate in vendor negotiations and manage external partnerships, as necessary. Qualifications Required: 10+ years of experience in data engineering, database architecture, or data analytics, including at least 5 years in a leadership role. Proven experience designing and managing enterprise-grade data warehouses (Snowflake, Azure, etc.). Deep knowledge of SQL, ETL design, data modeling, and integration methodologies (APIs, etc.). Demonstrated experience implementing data governance, security frameworks, and access control mechanisms. Ability to assess and optimize cloud cost structures (e.g., Snowflake storage vs. compute). Excellent strategic thinking, with the ability to balance near-term delivery with long-term scalability. Exceptional communication skills, especially in translating complex technical issues into business context. Preferred Familiarity with tools and systems like ClientSpace, Prism, iSolved, Salesforce, and other payroll or CRM platforms. Experience with AI/ML model enablement or automation tools (e.g., RPA, scripting). Experience integrating with global payroll platforms and managing data across international systems.