Project Manager, Data Team

Responsibilities

• Own end-to-end project management for data initiatives, including intake and scoping, requirements gathering, readiness reviews, cross-functional approvals, and launch/post-launch handoff.
• Take direct responsibility for the successful execution of projects, including meeting project goals, client/stakeholder service, quality of work, resource utilization, and profitability.
• Lead, motivate, and build a strong team environment for project contributors, inspiring a shared vision, enabling others to act, and taking ownership of team outcomes.
• Partner with team leads to vet, scope, and kick off assignments, and own all due dates and milestones.
• Develop and maintain accurate project documentation, including timelines, budgets, and scoping documents.
• Lead communications and change management across the project lifecycle, from kickoff briefings for stakeholders through end-user notifications ahead of launches, ensuring the right people have the right information at the right time.
• Serve as the primary coordination point across functional teams (Data Engineering, Analytics, Legal, Finance, etc.), aligning workstreams and driving decisions and accountability against timelines.
• Anticipate and manage the downstream implications of project decisions before they create risk; proactively surface dependencies, resolve blockers, and escalate when needed.
• Build and continuously improve the infrastructure that makes data project delivery scalable: intake forms, templates, checklists, SOPs/playbooks, and retrospectives that feed into process improvement.
• Manage relationships with key stakeholders to promote trust and future opportunities.

Requirements

• 3-5+ years of project management experience or related experience.
• Bachelor’s degree or equivalent experience in a related field.
• Excellent leadership, communication, and stakeholder management skills.
• Ability to work collaboratively across departments (engineering, data science, leadership, legal, finance).
• Superb attention to detail, sound judgment, and strong listening skills.
• Comfortable driving process improvement and proposing more efficient ways of working.
• Passion for data-driven products and cross-functional collaboration.

Nice-to-Haves

• Proven track record managing large, cross-functional data or technical projects.
• Experience managing a high volume of projects in parallel.
• Experience with data, engineering, or analytics project types.