Senior Manager of Data Strategy

Responsibilities

Strategic Vision: You are responsible for communicating the vision of our data solutions, creating buy-in for the product vision internally and with clients.

• Leads discovery and problem framing across workstreams, meeting with key client stakeholders to translate vision and business requirements into technical and analytical requirements
• Frames the roadmap around the client’s business goals, the urgency behind them, and the impact of acting (or not)
• Weighs the client’s AI readiness, including data quality, governance, and semantic layer maturity, alongside reporting and BI needs when shaping engagement priorities
• Delivers regular internal and external project status reports to key stakeholders and executives
• Develops data solutions positioning strategies, including business development initiatives such as product partnerships, proposal writing, client extensions, and other revenue-generating activities

Cross-Team Collaboration: You are responsible for collaborating with other functional departments to ensure alignment with the goals of the data engagement.

• Submits staffing requests to Resource Management to ensure the right team is in place to deliver against client needs
• Works with functional teams to design data architecture for clients and recommend appropriate infrastructure and tools; partners with technical leadership on complex or higher-risk architecture calls while independently handling more routine ones
• Manages cross-team dependencies and escalation paths across workstreams, and keeps developers across those workstreams supported and engaged

Engagement Delivery: You are responsible for translating our data solutions strategy into detailed requirements for other functional teams.

• Serves as the primary point of contact for managing, building, and maintaining positive client relationships
• Owns delivery governance across multiple workstreams/engagements, managing project schedules and team workload to optimize capacity and velocity
• Drives the successful delivery of client projects within defined budget, schedule, and scope with outstanding client satisfaction
• Manages the sprint board for each engagement, including backlog management, planning, and retrospectives
• Proactively identifies, tracks, and mitigates issues and risks, and provides strategies and recommendations
• Helps shape and scope account expansion (extensions, change orders), including AI-readiness assessments, in partnership with Client Services, contributing delivery and technical input while CS continues to lead overall account strategy

Technical Skills

Tool requirements: Intermediate proficiency across the core components of a modern data platform:

• Data ingestion SaaS (e.g., Fivetran, Stitch)
• Massively parallel processing data warehouse (e.g., Snowflake, BigQuery, Databricks)
• Data transformation tools (e.g., dbt, SQLMesh)
• Cloud-forward business intelligence platform (e.g., Tableau, Sigma, Looker)
• Leads low-to-moderate technical discoveries and articulates platform tradeoffs, helping stakeholders reach a decision; partners with technical leadership on complex or higher-risk architecture calls
• Assesses whether a client’s data models and pipelines are structured to support downstream AI and agentic use cases, such as clean entity definitions, feature-ready marts, and complete metadata, as part of infrastructure recommendations

Understands how the pieces above fit together to deliver value to the client, including the ability to weigh pros and cons from both a technical and business perspective. Senior Managers of Data Strategy are expected to deliver and articulate infrastructure recommendations aligned with a client’s business objectives.

Agile Professional: Well-equipped to tackle unforeseen situations and capable of jumping into projects and teams at any point in their development. May teach or mentor other managers on setting Agile goals, developing viable plans, and implementing Agile approaches, blending Agile with other PM frameworks as needed to ensure project delivery.

Skills & Qualifications

• 8–12 years of experience independently leading complex and broad-ranging data projects, across dimensions including cross-functional, multi-geographic, and long-duration engagements
• Strong project management skills, including experience operating in and building Agile and other frameworks
• Strong analytical, critical thinking, and creative capabilities
• Strong knowledge of the modern data stack and its components, including how to configure it and how it fits with non-modern data technologies (e.g., on-prem vs. cloud)
• Working familiarity with how AI and agentic workflows consume data (e.g., semantic layers), enough to evaluate architecture tradeoffs credibly
• Hands-on experience as an analyst, analytics engineer, data engineer, or similar
• Organized and process-oriented
• Available for occasional client travel, up to 10% of the time
• Ability to speak to all levels of prospective clients: strategic and tactical decision-makers
• Excellent interpersonal and communication skills