Data Product Manager

About the role

Axos Bank is seeking a VP, Data Product Manager to shape the next generation of our enterprise data platform. This role combines product thinking, data engineering fluency, and AI-driven delivery insights to help the team move faster, deliver smarter, and scale seamlessly.

Responsibilities

• 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.

Requirements

• 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., GitHub 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.

Preferred

• 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.