Managing Director, Enterprise Data & Analytics

Baker Tilly; San Francisco (CA); On-site; USD 350,000 - 550,000; Full time

Job summary

Baker Tilly is seeking a Managing Director of Enterprise Data & Analytics to lead data engineering, data platform, MDM, semantic modeling, reporting, and analytics capabilities.

Reporting to the CDIO, this leader will transform enterprise data into trusted assets enabling scalable AI, operational efficiency, and differentiated client experiences.

Qualifications

• 15+ years in data engineering, data platforms, or tech leadership.
• Proven ownership of production data platforms and governance.
• Experience with enterprise BI/reporting, data modeling, and data products.

Responsibilities

• Lead Databricks lakehouse strategy, architecture, and operations.
• Oversee Data Engineering, DataOps, and CI/CD for pipelines.
• Own enterprise data architecture with EA&G collaboration.
• Develop governed semantic layer with KPI standards and metrics.
• Lead enterprise MDM and data stewardship across domains.
• Oversee enterprise reporting and analytics for exec and ops.
• Enforce data governance, privacy, security, and QA controls.
• Partner with AI/TDIO teams to enable AI products with governed data.

Skills

Databricks lakehouse

Data governance

Enterprise data architecture

Leadership

AI data products

Education

Bachelor’s degree in Computer Science, Information Technology, Data Science, Engineering, or related field

Job description

Overview

Baker Tilly is a leading advisory, tax and assurance firm, providing clients with a genuine coast-to-coast and global advantage in major regions of the U.S. and in many of the world’s leading financial centers – New York, London, San Francisco, Los Angeles, Chicago and Boston. Baker Tilly Advisory Group, LP and Baker Tilly US, LLP (Baker Tilly) provide professional services through an alternative practice structure in accordance with the AICPA Code of Professional Conduct and applicable laws, regulations and professional standards. Baker Tilly US, LLP is a licensed independent CPA firm that provides attest services to its clients. Baker Tilly Advisory Group, LP and its subsidiary entities provide tax and business advisory services to their clients. Baker Tilly Advisory Group, LP and its subsidiary entities are not licensed CPA firms.

Baker Tilly Advisory Group, LP and Baker Tilly US, LLP, trading as Baker Tilly, are independent members of Baker Tilly International, a worldwide network of independent accounting and business advisory firms in 141 territories, with 43,000 professionals and a combined worldwide revenue of $5.2 billion. Visitbakertilly.comor join the conversation onLinkedIn,FacebookandInstagram.

Please discuss the work location status with your Baker Tilly talent acquisition professional to understand the requirements for an opportunity you are exploring.

Baker Tilly is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, gender identity, sexual orientation, or any other legally protected basis, in accordance with applicable federal, state or local law.

Any unsolicited resumes submitted through our website or to Baker Tilly Advisory Group, LP, employee e-mail accounts are considered property of Baker Tilly Advisory Group, LP, and are not subject to payment of agency fees. In order to be an authorized recruitment agency ("search firm") for Baker Tilly Advisory Group, LP, there must be a formal written agreement in place and the agency must be invited, by Baker Tilly's Talent Attraction team, to submit candidates for review via our applicant tracking system.

Job Description:

Baker Tilly is seeking a Managing Director of Enterprise Data & Analytics to lead the firm’s 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.

Responsibilities

• 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.

Qualifications

• Bachelor’s 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 $350,00-$550,000. Actual compensation is influenced by a variety of relevant factors including but not limited to applicant’s skills, prior experience, qualifications, degrees, professional certifications, work arrangements and geographic location. Baker Tilly offers a comprehensive compensation and benefits package to eligible employees.