Director, Data Center of Excellence

Momentive

1d•Remote

About The Position

This role is responsible for leading the enterprise data architecture and strategy, overseeing data migration projects, providing consulting services for data readiness and custom analytics, managing premium offerings and commercialization of insights, integrating third-party platforms and agentic AI, and providing organizational leadership. The Director will also ensure continuity for legacy clients during the transition framework and lead the creation and execution of cross-functional data best practices. Key performance deliverables include creating Data COE Playbooks and Technical Checklists, achieving Momentive IQ Professional Services revenue targets, meeting team billable utilization goals, and achieving client NPS scores.

Requirements

7+ years of progressive leadership experience in Data Architecture, Enterprise Analytics, Business Intelligence, or Data Strategy.
Demonstrated success in structuring and executing complex enterprise data migrations and third-party software integrations.
Bachelor’s or Master’s degree in Data Science, Computer Science, Information Systems, Business Administration, or an equivalent technical field.
Data management or governance certifications (e.g., DAMA‑CDMP).
Strategic understanding of BI tools, ETL architectures, cloud compliance, and modern agentic AI applications.
Proven ability to partner dynamically across Product, Engineering, Sales, and Customer Success silos to operationalize data products and services.
Exceptional communication, stakeholder management, and narrative-building skills capable of translating complex analytics into clear business actions.

Nice To Haves

Previous client-facing professional services or premium data consulting experience is highly preferred.

Responsibilities

Own, evolve, and scale the enterprise data architecture supporting all product verticals.
Establish standards, best practices, and repeatable patterns for data ingestion, transformation, and consumption.
Align data strategy directly with internal product roadmaps, engineering timelines, and advanced client analytics needs.
Define data migration scopes, constraints, historical requirements, and success criteria.
Design data mapping, transformation, enrichment, validation, and rollback protocols.
Partner with stakeholders to establish testing cycles, cutover plans, and client approvals.
Oversee extraction, transformation, and loading (ETL) into test, UAT, and production environments.
Lead iterative migration cycles, resolve technical anomalies, and manage post-migration hypercare/remediation.
Deliver comprehensive migration completion documentation and client sign-offs.
Assess source data usability; cleanse, normalize, and de-duplicate data sets to make them analytics-ready.
Translate complex business objectives into custom dashboards, defining metrics, visualizations, filters, and refresh cadences.
Advise clients on data collection methodologies (timing, frequency, automation) and practical data governance/stewardship operating frameworks.
Help define, manage, and mature the delivery workflows and quality standards associated with the Company’s AI Analytics subscription service offerings.
Operationalize benchmarking frameworks and peer-group analysis, translating data into executive-ready insights for priority customer segments.
Track measurable client outcomes to develop case studies; partner with Product, Marketing, and Sales to support go-to-market and thought-leadership activities.
Scope, prioritize, and support deal-driven integrations with third-party platforms to enhance workflow analytics.
Contribute to the creation, refinement, and client-facing alignment of agentic roles and AI-enabled capabilities.
Build out the core Data Strategy & Services operating models, documentation standards, and prioritization frameworks.
Maintain high-level Project Manager/Customer Engagement continuity for designated legacy accounts (requirements definition, risk management, internal coordination) during the initial transition framework.
Lead the creation and execution of cross-functional and cross-product data best practices.