Data Governance Lead - Senior ManagerRole Overview The
Data Governance Lead - Senior Manager is responsible for building, leading, and growing the firm's Data Governance capabilities while serving as a hands-on delivery leader on client engagements.
This role combines three primary responsibilities:
- Data Governance Consulting & Delivery - Lead client governance programs, workshops, workstreams, and deliverables.
- Data Governance Practice Development - Develop repeatable offerings, methodologies, accelerators, and solutions that can be taken to market.
- Databricks Practice & Alliance Leadership - Help establish and grow Databricks capabilities, solutions, partnership relationships, and associated revenue opportunities.
The ideal candidate combines strong consulting and client leadership skills with deep knowledge of enterprise data governance, modern cloud data platforms, Databricks, metadata management, data quality, and organizational change.
Data Governance Program Leadership Program Management - Own and manage enterprise Data Governance program roadmaps.
- Establish program priorities, milestones, deliverables, dependencies, and success metrics.
- Manage day-to-day workflows for the Data Governance Office (DGO).
- Maintain project plans, Jira boards, issue logs, decision logs, risks, and action items.
- Provide clear program status and executive-level reporting.
- Coordinate governance activities across multiple business and technology workstreams.
Governance Framework, Policy & Standards - Design, implement, and operationalize enterprise Data Governance frameworks.
- Data management standards
- Data classification standards
- Align governance frameworks with organizational strategy, regulatory requirements, and enterprise architecture.
- Apply governance frameworks and industry practices such as DAMA-DMBOK and DCAM.
Data Ownership & Stewardship - Design and implement enterprise Data Owner and Data Steward operating models.
- Define clear accountability for critical data domains and assets.
- Establish roles and responsibilities across business owners, technical owners, data stewards, and custodians.
- Develop stewardship processes, governance workflows, escalation paths, and decision-making models.
- Coach and support Data Owners and Stewards as governance programs mature.
Metadata, Catalog & Lineage - Lead enterprise metadata management and data catalog initiatives.
- Advise clients on governance technologies such as Collibra, Informatica, Alation, Microsoft Purview, and Databricks Unity Catalog.
- Connect business metadata with technical metadata to improve data discovery, trust, lineage, and accountability.
Data Quality - Establish enterprise Data Quality frameworks and standards.
- Define measurable data quality dimensions, rules, thresholds, and KPIs.
- Develop Data Quality scorecards and dashboards.
- Establish processes for identifying, prioritizing, remediating, and monitoring data quality issues.
- Partner with business and technical teams to implement preventative and detective data quality controls.
- Help organizations transition from reactive data cleansing to sustainable Data Quality Management.
Governance Councils & Executive Facilitation - Establish and facilitate Data Governance Councils, working groups, and steering committees.
- Prepare governance agendas, executive pre-reads, scorecards, and decision materials.
- Track council decisions, actions, issues, and escalations.
- Facilitate difficult cross-functional discussions involving data ownership, definitions, priorities, and accountability.
- Translate technical data issues into clear business risks, decisions, and recommendations for executive leadership.
Cross-Functional Leadership - Act as a bridge between executive leadership, business units, data teams, analytics teams, security, legal, compliance, architecture, and engineering organizations.
- Translate business objectives into practical governance requirements and operating models.
- Partner with Information Security and Privacy teams to align governance processes with regulatory and security requirements.
- Support governance and compliance requirements associated with regulations such as:
- Other applicable industry or institutional requirements
- Drive organizational change and adoption of new governance processes.
- Develop training, communications, and stakeholder engagement strategies that make governance operational rather than theoretical.
Data Governance Consulting & Client Delivery The Senior Manager must remain
client-facing and billable and be capable of directly leading Data Governance engagements.
Engagement Delivery - Serve as the Data Governance Lead on client engagements.
- Lead governance workstreams from discovery through implementation.
- Plan and facilitate client workshops with executive, functional, and technical stakeholders.
- Lead current-state assessments and governance maturity assessments.
- Develop future-state governance models and implementation roadmaps.
- Own the quality and completion of client deliverables.
- Manage consultants and analysts supporting governance engagements.
- Provide executive-level recommendations and presentations.
Typical Client Deliverables Lead the creation and delivery of:
- Governance Operating Model
- Data Owner and Stewardship Model
- Data Classification Standards
- Critical Data Element Framework
- Metadata Management Strategy
- Governance Council Structure
- Governance KPIs and Metrics
- Governance Training and Adoption Plans
Data Governance Practice Development A key responsibility of this position is to
build and grow marketable Data Governance solutions and offerings.
Offering Development - Develop packaged Data Governance consulting offerings that can be consistently sold and delivered.
- Create repeatable methodologies, templates, accelerators, assessments, and delivery frameworks.
- Develop offerings around areas such as:
- Data Governance Strategy & Roadmap
- Governance Maturity Assessments
- Data Governance Operating Models
- Databricks Governance / Unity Catalog
- Create estimates, delivery models, staffing plans, and standard scopes of work.
- Develop reusable intellectual property that improves delivery speed and consistency.
Business Development & Pre-Sales - Support sales opportunities as the Data Governance subject matter expert.
- Lead discovery sessions with prospective clients.
- Identify client challenges and translate them into consulting opportunities.
- Develop solution approaches, estimates, proposals, and statements of work.
- Participate in client presentations, demonstrations, RFP responses, and executive meetings.
- Partner with account executives and consulting leadership to identify expansion opportunities within existing accounts.
Databricks Practice Leadership The Senior Manager will also help develop and grow the firm's
Databricks consulting capabilities and partner channel.
Strategy & Growth - Help define the firm's Databricks go-to-market strategy and service offerings.
- Build a pipeline of Databricks consulting opportunities through direct clients and the Databricks partner ecosystem.
- Develop relationships with Databricks account executives, solution architects, partner teams, and leadership.
- Work with sales leadership to develop and maintain a $2M-$3M+ annual Databricks opportunity pipeline and sales target.
- Identify opportunities where Databricks can support:
- Enterprise data platforms
- Support Databricks-focused proposals, scoping, estimates, demonstrations, and executive presentations.
Databricks Architecture & Advisory - Provide technical leadership for enterprise Databricks solutions.
- Design and advise on scalable Lakehouse architectures.
- Establish modern Bronze / Silver / Gold medallion architectures.
- Support architectures across AWS, Azure, and Google Cloud environments.
- Establish security, governance, data access, and operational standards for Databricks environments.
Databricks Governance - Connect enterprise Data Governance strategies with Databricks platform capabilities.
- Advise clients on implementing governance through Unity Catalog.
- Establish approaches for Data ownership, Data classification, Access controls, Metadata, Data lineage, Data discovery, Data quality, Data sharing
- Position governance as a foundational component of Databricks and enterprise AI/data modernization programs.
Practice Development - Build reusable Databricks reference architectures, accelerators, frameworks, and delivery methodologies.
- Establish technical standards and delivery best practices.
- Develop reusable deployment and implementation patterns.
- Build packaged Databricks offerings that can be sold through both direct sales and the Databricks partner channel.
- Develop internal training and certification strategies to expand Databricks capabilities across the consulting organization.
- Mentor architects, engineers, consultants, and technical delivery leaders.
Required Skills & Qualifications Data Governance - 7+ years of experience in Data Governance, Data Management, Data Quality, Metadata Management, or enterprise data programs.
- Demonstrated experience leading enterprise Data Governance programs.
- Strong understanding of frameworks such as DAMA-DMBOK and DCAM.
- Experience establishing Data Owner and Data Steward operating models.
- Experience developing governance policies, standards, procedures, and controls.
- Experience with metadata, business glossaries, data catalogs, lineage, and data quality.
- Experience with platforms such as Collibra, Informatica, Alation, Microsoft Purview, or similar technologies.
Databricks & Modern Data Platforms - Strong knowledge of modern cloud data platforms and Lakehouse architectures.
- Experience with or strong knowledge of Databricks, Delta Lake, Unity Catalog, Spark, PySpark, SQL, and modern ETL/ELT architectures.
- Understanding of cloud environments including A
