Managing Director, Enterprise Data & Analytics

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Baker Tilly is seeking a Managing Director of Enterprise Data & Analytics to lead the firms enterprise data engineering data platform master data management semantic modeling reporting and analytics capabilities.

Reporting directly to the Chief Digital & Information Officer (CDIO) this leader will transform enterprise data into a trusted reusable and well-governed asset that enables business decisions scalable AI operational efficiency and differentiated client and practitioner experiences.

This role will own the enterprise data architecture and implementation roadmap in partnership with Enterprise Architecture & Governance (EA&G) ensuring consistent standards across data pipelines data products semantic models master data and analytics solutions.

The Managing Director will oversee both Data Engineering and Enterprise Data Analytics unifying platform engineering and enterprise insight delivery under one accountable leader. This individual will partner closely with technology AI security risk finance and business leaders to build a scalable enterprise data foundation that supports innovation enterprise-wide analytics and public-company readiness.

• Lead the strategy architecture engineering and operations of the enterprise Databricks lakehouse ensuring scalability reliability security performance and cost efficiency through a disciplined bronze/silver/gold medallion architecture.
• Oversee enterprise data engineering integration and DataOps including ingestion transformation orchestration testing CI/CD observability and operational support for enterprise data pipelines.
• Own enterprise data architecture in partnership with EA&G establishing data domains integration patterns authoritative sources data contracts metadata lineage and reusable enterprise data products.
• Develop and maintain a governed semantic layer with standardized business definitions certified KPIs conformed dimensions and consistent metrics to support enterprise reporting self-service analytics and AI applications.
• Lead the implementation and operation of enterprise master data management (MDM) including entity resolution golden records reference data stewardship workflows and master-data synchronization across key business domains.
• Oversee enterprise reporting dashboards and analytics solutions partnering with business leaders to deliver trusted executive operational financial workforce client and service-line insights.
• Implement and enforce enterprise data governance privacy security and protection standards established by EA&G and approved governance bodies including access controls data quality retention lineage and auditable processes.
• Partner with Security Risk Legal Privacy Compliance and Finance to establish evidence-ready data and reporting controls supporting regulatory requirements audit readiness and IPO/public-company expectations.
• Collaborate with the Chief AI and Technology Officer (CAITO) AI Product Group (APG) and TDIO teams to provide governed data products data contracts BTID-linked entities and scalable data services that enable AI generative AI and agentic applications.
• Establish measurable service levels and operational standards for data availability freshness accuracy recovery and platform reliability while continuously improving data quality and consumption.
• Lead and develop multidisciplinary Data Engineering and Enterprise Data Analytics teams fostering accountability technical excellence collaboration and consistent delivery practices across US and global teams.
• Manage enterprise data investments vendor partnerships platform consumption capacity planning and technology roadmaps while aligning priorities with business outcomes and strategic objectives.

• Bachelors degree in Computer Science Information Technology Data Science Engineering or a related field required.
• 15 years in data engineering data platforms enterprise data architecture analytics or technology leadership including significant enterprise-wide people and budget leadership.
• Proven ownership of a production Databricks lakehouse and medallion architecture including scalable engineering governance observability performance and FinOps.
• Demonstrated application of site reliability engineering practices to enterprise data platforms including service-level objectives error budgets automated observability incident response root-cause analysis and tested recovery. Candidates can substantiate improvements in data freshness availability recovery time and cost per workload from platforms they have operated.
• Deep experience with enterprise semantic modeling governed business metrics modern BI/reporting and enterprise data products.
• Demonstrated implementation and operational ownership of enterprise MDM entity resolution golden records and business stewardship.
• Experience integrating ERP CRM HR finance and other systems of record in a complex multi-business organization.
• Credibility in IPO-ready or publicly traded company environments including data/reporting control design ITGC/SOX-relevant processes audit evidence financial-data lineage change controls and collaboration with Finance and auditors.
• Experience operationalizing data privacy and protection standards with Legal Risk Security and Privacy stakeholders.
• Experience translating approved data governance privacy and security policies into automated testable platform controls including policy-as-code entitlement validation lineage checks retention and deletion enforcement and continuously generated audit evidence. Demonstrated ability to detect control failures within delivery pipelines and remediate them with EA&G Security Legal and Privacy stakeholders.
• Experience enabling AI/ML and generative AI programs with governed enterprise data reusable contracts high-quality datasets and production service levels.
• Demonstrated delivery of enterprise data services consumed by production generative AI and agentic applications with evidence of permission-aware access source provenance reproducible evaluation datasets freshness controls and measurable improvements in data-related response quality.
• Experience partnering with AI product teams while retaining accountability for the enterprise data foundation rather than product-specific AI architecture.
• Strong record of influencing executive stakeholders and leading complex operating-model and data modernization transformations.
• Professional services financial services or other regulated and data-intensive industry experience preferred.

The national pay rate range for this job position is $35000-$550000. Actual compensation is influenced by a variety of relevant factors including but not limited to applicants skills prior experience qualifications degrees professional certifications work arrangements and geographic location. Baker Tilly offers a comprehensive compensation and benefits package to eligible employees.