ZipRecruiter

Log In

1

Data Project Manager Jobs in California (NOW HIRING)

Abaka AI

Project Manager

Mountain View, CA · On-site

Abaka AI is built on one mission: to be the world's most trusted data partner for AI companies. They are seeking a Project Manager who will ensure the successful delivery of data projects for leading ...

Drunix Solution Inc

AI project Manager

San Jose, CA · On-site

$60.75 - $82/hr

Project Manager - Data & AI Initiatives 📍 Location: San Jose, CA 🏢 Work Model: 4 Days Onsite 📄 Type: Contract 📩 Send resumes to: We are looking for a strong Project Manager with exposure ...

New

previous pagenext page

Showing results 21-40

All JobsData Project JobsData Project Manager JobsData Project Manager Jobs in California

Data Project Manager information

See California salary details

$16

$56

$79

How much do data project manager jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for data project manager in California is $56.75, according to ZipRecruiter salary data. Most workers in this role earn between $49.09 and $66.44 per hour, depending on experience, location, and employer.

How does a data project manager typically collaborate with data analysts, engineers, and stakeholders during a project lifecycle?

A Data Project Manager acts as the central point of coordination between technical teams—like data analysts and engineers—and business stakeholders. They facilitate regular meetings to clarify project goals, align on deliverables, and resolve blockers swiftly. The role often involves translating business requirements into actionable tasks for the technical team, monitoring progress, and ensuring that communication flows smoothly among all parties. This collaborative approach helps ensure data projects are delivered on time and meet organizational objectives.

What is the difference between Data Project Manager vs Data Analyst?

AspectData Project ManagerData Analyst
Required CredentialsBachelor's in Business, IT, or related field; PMP or project management certifications often preferredBachelor's in Statistics, Mathematics, or related field; often requires proficiency in data analysis tools
Work EnvironmentOversees projects, manages teams, coordinates between stakeholdersAnalyzes data sets, creates reports, visualizations, and insights
Employer & Industry UsageUsed across industries for managing data projects in tech, finance, healthcareCommonly employed for data interpretation and reporting roles in similar industries

The Data Project Manager focuses on planning, executing, and closing data-related projects, ensuring timely delivery and stakeholder communication. In contrast, a Data Analyst primarily interprets data, creates reports, and provides insights. Both roles require strong analytical skills, but their responsibilities and focus areas differ significantly.

What does a data project manager do?

A Data Project Manager oversees data-related projects, ensuring they are completed on time, within budget, and according to specified requirements. They coordinate teams of data analysts, engineers, and other stakeholders to collect, manage, and analyze data. Their responsibilities include project planning, risk management, resource allocation, and communication with clients or leadership. Data Project Managers play a crucial role in transforming raw data into actionable insights for organizations.

What are the key skills and qualifications needed to thrive as a data project manager, and why are they important?

To thrive as a Data Project Manager, you need strong project management abilities, data analysis skills, and a relevant degree in business, information technology, or a related field. Familiarity with project management tools (like Jira or Asana), data visualization platforms (such as Tableau or Power BI), and certifications like PMP or Agile/Scrum are commonly required. Exceptional communication, leadership, and problem-solving skills help drive cross-functional collaboration and resolve complex project challenges. These skills are crucial for ensuring projects are delivered on time, data is leveraged effectively, and stakeholder expectations are met.
What are popular job titles related to Data Project Manager jobs in California? For Data Project Manager jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Project Manager jobs in California look for? The top searched job categories for Data Project Manager jobs in California are:
What cities in California are hiring for Data Project Manager jobs? Cities in California with the most Data Project Manager job openings:
Data Project Manager jobs near you
Infographic showing various Data Project Manager job openings in California as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $118,050 per year, or $56.8 per hour.

US - Program Manager - Data Solutions (AI PMO

AuxoAI Inc

Irvine, CA • On-site

$120K/yr

Full-time

Posted 5 days ago

Job description


About AuxoAI
AuxoAI helps enterprises transform how they operate by combining business consulting, data, engineering, and Agentic AI. We are building an AI-native consulting model in which every team member is expected to use AI thoughtfully to improve speed, insight, quality, and client outcomes.
What You Will Do
• Maintain the integrated delivery plan for data migration, conversion, cleansing, reconciliation, and validation activities.
• Coordinate business data owners, source-system teams, data engineers, functional teams, testing teams, and the System Integrator.
• Track data objects, conversion cycles, mock loads, entry and exit criteria, defects, reconciliations, and business sign-offs.
• Manage dependencies between source extraction, transformation rules, Oracle load processes, downstream validation, and cutover sequencing.
• Facilitate data readiness reviews and drive resolution of quality, mapping, ownership, timing, and environment issues.
• Prepare concise status reporting on conversion progress, data quality, open defects, reconciliation results, and readiness risks.
• Support SIT, UAT, business simulation, cutover rehearsals, production migration, and hypercare validation.
• Ensure decisions, assumptions, mapping changes, and unresolved data issues are traceable and assigned to accountable owners.
AI-Enabled Delivery Responsibilities
• Use AI to summarize mapping documents, identify conflicting transformation rules, and highlight incomplete data ownership decisions.
• Generate AI-assisted conversion status narratives, reconciliation summaries, defect themes, and data-quality risk insights.
• Apply AI to compare source-to-target specifications, workshop decisions, and test evidence for traceability gaps.
• Develop repeatable prompts or workflows that improve the speed and consistency of data PMO activities.
Common AI-First Expectations at AuxoAI
• Use enterprise AI tools such as ChatGPT Enterprise, Claude Enterprise, Gemini, or equivalent platforms to accelerate delivery and improve decision-making.
• Apply AI to automate meeting summaries, action-item tracking, status reporting, executive communications, and document synthesis.
• Use AI-assisted analysis to identify delivery risks, cross-team dependencies, emerging bottlenecks, and areas requiring leadership attention.
• Continuously identify PMO activities that can be simplified, standardized, or automated through AI and workflow automation.
• Validate AI-generated outputs for accuracy, confidentiality, traceability, and business relevance before they are used in program decisions.
• Collaborate with consulting, data, engineering, and AI teams to pilot and scale AI-enabled delivery practices across the program.
Requirements
• 4-6 years of experience in project coordination, project management, data delivery, or enterprise transformation.
• Understanding of data migration concepts including extraction, cleansing, mapping, conversion, validation, and reconciliation.
• Experience coordinating cross-functional teams and tracking milestones, dependencies, risks, issues, and decisions.
• Strong Excel, documentation, analytical, and communication skills.
• Ability to translate technical data issues into clear business and program impacts.
• Comfort using AI tools to analyze documents, summarize findings, and improve reporting.
Preferred Qualifications
• Experience with Oracle Fusion data conversion, FBDI, ADFdi, or related Oracle data-load methods.
• Exposure to SQL, ETL/ELT, Snowflake, Informatica, Oracle Integration Cloud, or similar platforms.
• Experience supporting mock conversions, reconciliations, SIT, UAT, or cutover.
• Experience with Jira, Azure DevOps, Power BI, Tableau, Smartsheet, or Microsoft Project.
• Familiarity with data governance, data quality, and master data management.
What Success Looks Like
• Clear delivery visibility
• Early risk identification
• Responsible AI adoption
• Predictable workstream outcomes

Apply