Data Strategy And Governance Director

Forrester•Cambridge, MA

1d•$130,000 - $212,000

About The Position

We are seeking a Data Strategy And Governance Director to be a critical member of Forrester’s go-to-market operations, working in conjunction with finance and IT. The Data Strategy And Governance Director will lead Forrester’s operational data strategy across product, marketing, sales, and customer success. The role will be accountable for overall data strategy within the marketing and sales databases and related systems, executing initiatives to improve data quality, unification, accessibility, and enablement. The role requires a deep understanding of how data supports product, marketing, sales, and customer success processes. This person will also play a central role in documenting the business context layer necessary to prepare data for advanced AI use cases within Forrester to better serve our clients. In addition, the Data Strategy And Governance Director will oversee the daily maintenance of operational data, define and enforce data governance policies as a key member of the data governance committee, and ensure data consumers can readily access high-quality data.

Requirements

At least 10 years’ experience, including a director-level or above position, in B2B data management leadership, revenue operations, go-to-market operations, marketing and sales analytics, and/or project management.
Proven experience in driving data quality initiatives, unifying data from disparate systems and finding new ways to provide data consumers easy access to the information they need.
Experience in aligning data with marketing and sales business processes.
Experience in designing data governance processes for data management by stewards, custodians, IT, and business data consumers.
Experience in cleansing data, as well as designing and executing data unification strategies.
Experience with LLMs, MAP, CRM, MDM/CDP, web, BI, data warehouse, CPQ, revenue orchestration, and sales performance management systems.
Creative problem-solving skills with high-level attention to detail.
The ability to work cross-functionally as well as across geographies and cultures.
Strong verbal and written communication skills: able to explain complex data management and data governance concepts to both technical and nontechnical stakeholders, audiences, and executive team members.
Strong project management skills.
Strong networking and stakeholder management skills.
The ability to work with business owners (data enablers) and data consumers to define data and reporting requirements.
Understanding of roadmap development and prioritization.
Budget management.
Data storytelling.
Comfortable working in a cross-functional and matrixed environment.

Responsibilities

Define Forrester’s operational data strategy.
Evaluate and identify data quality, integrity, and accessibility issues and coordinate and implement corrections across company systems and channels, including process improvement, access management, and ongoing data enablement.
Evaluate and identify data privacy, security, and regulatory issues and implement corrections across company systems and channels to support company privacy policies.
Coordinate and maintain ongoing/regular relationships, communication, and processes with subject matter experts and leads across lines of businesses as well as finance, technology, analytics, legal and compliance, and security and operations (SecOps) teams to create, design, apply, and manage data policies.
Establish ongoing coordination across functions, particularly technology teams, to ensure visibility into changes to data and architecture.
Create and communicate the measurement plan for data management, including database readiness metrics and metrics that capture the impact of database readiness on downstream product, marketing, sales, and customer success processes.
Support the documentation, cleansing, and construction of the data layer and marketing and sales business context layer necessary to support LLM model development.
Define the data acquisition strategy to ensure that desired levels of breadth and quality are achieved.
Provide subject matter expertise for AI data and business context development and internal quality control.