Data Analytics Project Manager Jobs in California

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SUMMARY:

The Project Manager, Data & Analytics is responsible for leading the planning, execution, and delivery of data and analytics initiatives that support AmaWaterways’ Value Creation Plan and Long-Range Plan objectives. This role manages the end-to-end project lifecycle for data platform buildouts, analytics product development, business intelligence tooling, and data governance programs, coordinating across Engineering, Analytics, Business, and external consulting partners. Working at the intersection of business strategy and technical execution, this role ensures that data and analytics investments are delivered on time, within scope, and calibrated to drive measurable performance improvement across the enterprise. The ideal candidate brings strong technical program management experience in data-intensive environments, familiarity with modern data platforms(Snowflake) and BI tools(Tableau, Snowflake,etc.), and the ability to translate between business stakeholders and technical teams.

The Project Manager, Data & Analytics will work closely with (dotted line) to the head of PMO who reports to the CTO.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Data & Analytics Platform Delivery

• Manage the end-to-end project lifecycle for data platform and analytics initiatives, including the Enterprise Data Warehouse, business intelligence dashboards, automated data feeds, and reporting infrastructure.

• Coordinate with Engineering, Analytics, and Architecture teams to plan and execute data product development, data on-boarding from source systems, and platform enhancements using Agile methodologies.

• Drive delivery of analytics products and services, including Tableau dashboards, KPI reporting frameworks, and advanced analytics capabilities that support VCP and LRP performance visibility.

• Manage the technical roadmap for data platform and analytics platform evolution, ensuring alignment between near-term deliverables and the target-state architecture (data architecture, advanced analytics architecture, AI platform alignment).

Data Governance & Master Data Management

• Support the implementation and maturation of data governance frameworks, including data stewardship RACI models, report governance standards, and data quality processes.

• Coordinate master data management initiatives and gold reference model development to ensure accurate, congruent data across the enterprise.

• Track data governance maturity against the target operating model, identifying gaps and driving remediation plans across business and technology stakeholders.

Operating Model Transformation

• Serve as the project management lead for the Data & Analytics operating model transformation, coordinating discovery, analysis, and activation phases with external consulting partners.

• Manage stakeholder interview schedules, documentation reviews, and collaborative assessments across all eight operating model areas: business/technology strategy, performance improvement metrics, products & services, platform & architecture, roadmaps, organization design & talent, collaboration model, governance, and portfolio management & funding.

• Track implementation of target operating model recommendations, ensuring change initiatives are tied to measurable performance improvement and key outcomes.

• Coordinate on-site workshops and off-site discussions to socialize findings, present recommendations, and refine activation plans with leadership.

Business Intelligence & Performance Metrics

• Manage delivery of business KPI dashboards and metrics trackers, including website analytics, consumer acquisition metrics, revenue management data, and VCP performance indicators.

• Coordinate the formalization of data inputs, metric definitions, and automated data feeds to ensure reporting accuracy and timeliness.

• Partner with business stakeholders across Marketing, Sales, Revenue Management, and Operations to translate analytical requirements into actionable data products.

AI & Advanced Analytics Initiatives

• Project-manage AI-related initiatives including AI-Powered Agent Assist (vendor selection, proof-of-concept, implementation) and AI platform integration planning.

• Coordinate with data science and engineering teams on advanced analytics product delivery, ensuring proper data pipelines, model infrastructure, and deployment workflows.

• Track the AI alignment roadmap and ensure AI initiatives are integrated with the broader data platform strategy.

Cross-Functional Coordination

• Direct cross-functional coordination between Data & Analytics, IT, Marketing, Sales, Finance, and Operations teams to align data initiatives with business priorities.

• Maintain portfolio management visibility across all data and analytics investments, providing regular status updates, budget tracking, and risk assessments to leadership.

SUPERVISORY RESPONSIBILITIES:

This role does not have direct reports but serves as the project lead coordinating data engineers, analysts, data scientists, and external consulting and vendor partners. Responsible for driving accountability across cross-functional workstreams and facilitating collaboration between technical and business teams. As the data organization matures per the target operating model, this position may expand to include direct management of project coordinators or junior analysts.

COMPETENCIES :

• Analytical Thinking – Synthesizes complex information; leverages data, experience, and sound judgment to design practical and effective solutions.

• Quality & Accountability – Delivers accurate, thoughtful work; applies feedback to improve outcomes; maintains high standards while balancing efficiency.

• Dependability – Takes ownership of responsibilities; follows through on commitments; meets deadlines; communicates proactively when circumstances shift.

• Collaboration & Teamwork – Partners effectively across teams and functions; values diverse viewpoints; builds trust; advances shared goals and collective success.

• Business Acumen – Understands the broader business impact of decisions; considers financial, market, and operational implications; aligns work with strategic priorities.