VP, Data Product Manager

• Location:
  
  Onsite in La Jolla, San Diego (candidate must be local or willing to relocate)
• Pay: $120-140k + 20% bonus

We are seeking a VP, Data Product Manager, to shape the next generation of our enterprise data platform. You'll combine product thinking, data engineering fluency, and AI-driven delivery insights to help the team move faster, deliver smarter, and scale seamlessly. This role bridges strategy and execution - owning the roadmap, backlog, and outcomes that enable analytics, AI, and business innovation across the organization.

• Own and manage the data engineering backlog-prioritize stories, define acceptance criteria, and ensure delivery of pipelines and platform capabilities that accelerate data availability and quality.
• Partner with Business Units, Analytics, and Tech Leadership to ensure data products are trusted, timely, and aligned with business priorities.
• Collaborate with Data Engineers, Tech Leads, and Architects to translate technical vision into actionable deliverables for ingestion, transformation, orchestration, and serving layers.
• Advocate for governed, scalable, and AI-ready data-partnering with Collibra and platform teams to ensure compliance and discoverability.
• Champion AI-assisted development and automation (e.g., dbt auto-tests, Databricks notebooks, CI/CD intelligence, metadata lineage) to improve team velocity and reduce manual workload.
• Leverage AI/ML-based monitoring and observability tools to enhance data reliability, anomaly detection, and operational performance.
• Drive the Data Platform roadmap, aligning across engineering, analytics, and business stakeholders with clear transparency and measurable impact.
• Foster a culture of continuous improvement, using metrics and retrospectives to increase throughput, quality, and predictability of delivery.
• Represent the engineering voice in cross-functional planning and communicate technical dependencies, risks, and opportunities clearly.
• Mentor junior Scrum Masters and influence agile practices to enhance team productivity and engagement.

• A transparent and trusted roadmap for the data platform.
• Consistent, high-quality, and governed data delivery.
• Improved team velocity and reduced cycle time through automation and AI augmentation.
• Strong relationships and alignment across business, analytics, and engineering.
• A scalable, AI-enabled platform foundation supporting future data products and innovation.

• 5+ years of experience in Data Engineering, Product Ownership, or Technical Program Management roles within modern data environments.
• Hands-on familiarity with Databricks, dbt, Fivetran, Kafka, Census, Azure Data Services, SSIS, Tableau, and Collibra.
• Experience leveraging AI-assisted tools (e.g., Git Hub Copilot, ADO, Databricks Assistant, or similar) to boost productivity and code quality.
• Strong grasp of data architecture, pipelines, orchestration, and governance frameworks.
• Proven ability to manage backlogs, define roadmaps, and drive delivery through Agile methodologies.
• Excellent communication and stakeholder management skills across technical and non-technical audiences.

• Experience working in financial services or regulated data ecosystems.
• Exposure to Lakehouse architectures, metadata-driven automation, and AI Ops for data platforms.
• Certifications such as CSPO, SAFe POPM, or Cloud certifications are advantageous.

All qualified applicants will receive consideration for employment without regard to race, color, national origin, age, ancestry, religion, sex, sexual orientation, gender identity, gender expression, marital status, disability, medical condition, genetic information, pregnancy, or military or veteran status. We consider all qualified applicants, including those with criminal histories, in a manner consistent with state and local laws, including the California Fair Chance Act, City of Los Angeles' Fair Chance Initiative for Hiring Ordinance, and Los Angeles County Fair Chance Ordinance.