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Position summary

The Project Manager, Data Analysis is responsible for planning, coordinating, and delivering data-focused projects that drive business decisions and operational improvements. This role sits at the intersection of analytics, business stakeholders, and engineering, ensuring that requirements are clear, timelines are realistic, and analytical outputs are accurate, actionable, and successfully adopted.

Key responsibilities

• Project ownership & planning

  • Own the end-to-end delivery of data and analytics projects from intake through deployment and post‑launch review.

  • Translate business questions into clear project charters, requirements, and success metrics.

  • Build and maintain project plans, including scope, milestones, dependencies, resourcing, and risk management.

• Stakeholder management

  • Partner with business leaders to prioritize requests, set expectations, and communicate status, risks, and trade‑offs.

  • Facilitate requirements workshops, design reviews, and readouts to align teams on goals and deliverables.

  • Act as the primary point of contact between business stakeholders, analytics teams, data engineering, and IT.

• Execution & coordination

  • Coordinate the work of data analysts, data engineers, and subject matter experts to ensure timely, high‑quality deliverables.

  • Ensure project documentation (requirements, data dictionaries, dashboards specs, runbooks) is created and maintained.

  • Proactively identify and resolve blockers related to data quality, tooling, access, or competing priorities.

• Data quality, governance & process

  • Partner with data owners to define and enforce data quality standards, validation checks, and SLAs.

  • Help design and refine repeatable processes for intake, estimation, prioritization, and QA of analytics work.

  • Support adoption of common definitions, metrics, and visualization standards across teams.

• Measurement & continuous improvement

  • Define and track KPIs for each project (e.g., usage, decision impact, time‑to‑insight) and report back to stakeholders.

  • Conduct post‑implementation reviews and retrospectives; capture lessons learned and drive process improvements.

  • Identify opportunities to templatize or automate recurring analytics work.

Qualifications

• Experience

  • 4–7+ years of experience in project or program management with a strong focus on data, analytics, or BI initiatives.

  • Hands‑on experience working with data/analytics teams (e.g., BI, data science, data engineering) in a product, operations, or consulting environment.

  • Proven track record managing multiple concurrent projects with cross‑functional stakeholders.

• Skills

  • Strong understanding of analytics concepts (e.g., KPIs, data modeling basics, dashboards, A/B testing) and common tools (e.g., SQL, BI platforms such as Tableau, Power BI, Looker, etc.) — enough to translate between technical and non‑technical audiences.

  • Excellent project management skills: scoping, estimation, dependency management, risk tracking, and stakeholder communication.

  • Clear, concise written and verbal communication, including comfort presenting to senior stakeholders.

  • Ability to analyze ambiguous problems, structure them into workstreams, and drive them to resolution.

• Education

  • Bachelor’s degree in Business, Analytics, Statistics, Computer Science, Information Systems, or a related field; equivalent experience considered.

Preferred qualifications

• Experience in a SaaS, technology, or data‑centric organization.

• Familiarity with modern data stacks (e.g., cloud data warehouses, ETL/ELT tools, reverse ETL, dbt).

• Formal project management training or certification (e.g., PMP, Scrum Master) is a plus.

Reporting & location

• Reports to: Director or Senior Manager of Analytics / Data / Business Operations (title configurable).

• Location: [Insert location or remote policy].

• Employment type: Full‑time, exempt.