Product owner, Data Platform and Data Products
Hapi (Data Travel, LLC) is looking for a technically-minded Product Owner to join our Engineering organization and drive the strategy, prioritization, and delivery of our Data Platform and Data Products. This is a hands-on, highly collaborative role embedded within our Data Engineering team, working at the intersection of data infrastructure and business value.
You will own the end-to-end backlog for our AWS-native data platform, from raw data ingestion and pipeline orchestration through data cataloging, governance, and the delivery of APIs and insights that power both internal teams and customer-facing products. You will be the connective tissue between Engineering, Product Management, Data Analysts, Solutions Architecture, and Implementation/Support. You will translate complex technical requirements into clear, actionable work while keeping the broader roadmap aligned with business priorities.
This is not a purely strategic role. You will be in the details: co-authoring tickets with engineers, triaging data quality issues, reviewing pipeline specs, and ensuring delivery stays on track. If you thrive in a fast-paced, technical environment and care deeply about data as a product, this role is for you.
Key Responsibilities
Backlog Ownership & Agile Delivery- Own and maintain the data platform product backlog, ensuring it is well-prioritized, visible, and aligned with both technical and business objectives.
- Co-author epics, features, and user stories with Data Engineers, including clear acceptance criteria, data contracts, and technical specifications.
- Facilitate sprint planning, backlog grooming, and retrospectives in partnership with the Data Engineering team lead.
- Actively triage incoming requests from Product Management, Data Analysts, Solutions Architecture, and Implementation/Support, translating them into actionable backlog items.
- Remove blockers and escalate risks or delivery challenges proactively to the Head of Engineering.
- Define and prioritize requirements for AWS-native data ingestion pipelines, ETL/ELT workflows, and data lake architecture, in close collaboration with Data Engineers.
- Own the data catalog and governance backlog, ensuring data assets are documented, discoverable, and reliable for downstream consumers.
- Drive requirements for data quality frameworks, monitoring, and SLA definitions across platform pipelines.
- Partner with Application Engineering to ensure data products and APIs are integrated effectively into customer-facing and internal systems.
- Translate business and analytical requirements from Data Analysts and Product Managers into clearly defined data product specifications, including datasets, APIs, and dashboard-ready outputs.
- Define success metrics for data products and monitor adoption, quality, and performance post-launch.
- Ensure data products meet the latency, reliability, and scalability requirements of a high-volume SaaS environment.
- Collaborate with the Product Management team and Solutions Architecture to maintain a coherent data platform roadmap, balancing near-term delivery with long-term platform health.
- Serve as the primary point of contact for Implementation and Support teams on data-related questions, bugs, and feature requests.
- Provide regular, transparent updates on platform progress, risks, and upcoming milestones to Engineering leadership and cross-functional stakeholders.
- Gather feedback from internal and external data consumers to inform continuous platform improvement.
Skills, Knowledge and Expertise
- 2-4 years of experience as a Product Owner or Product Manager with direct ownership of data engineering, data platform, or data infrastructure products.
- Hands-on experience working within Agile/Scrum teams as a PO - writing and refining tickets, running sprint ceremonies, and managing a live backlog.
- Strong working knowledge of modern cloud-native data architectures, including data lakes, lakehouses, and ELT/ETL pipeline patterns.
- Practical experience with AWS data services (e.g., S3, Glue, Athena, Air Flow, DynamoDb, Aurora Clusters, etc.) - AWS Cloud Practitioner certification is a plus.
- Ability to read and critically evaluate data pipeline logic, data models, and schema definitions - you don't need to write production code, but you need to understand what engineers are building.
- Experience defining data contracts, data quality requirements, or SLA frameworks for data pipelines.
- Proven ability to bridge technical data engineering teams and non-technical business stakeholders, translating between both directions fluently.
- Experience with Jira for backlog management and sprint tracking.
- Strong written and verbal communication skills, with a track record of producing clear, concise technical documentation and requirements.
- Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field — or equivalent practical experience.
- Experience with data catalog or data governance tooling
- Familiarity with data API design - REST or GraphQL - and experience defining requirements for data product delivery via APIs.
- Experience in or strong understanding of the hospitality industry
- Familiarity with hospitality data standards such as HTNG, or experience integrating with Property Management Systems (PMS).
- Experience working with Solutions Architecture teams on multi-tenant SaaS platform design.
- Experience in a fast-paced growth-stage company or working with modular, platform-based product architectures.