Technical Product Owner – Data Platforms

Job Description 

a.       Product Ownership & Delivery Management

• Define, manage, and prioritize the product backlog (epics, features, user stories) in alignment with the Data Layer Lead.
• Maintain and continuously refine the product roadmap in alignment with the Data Layer Lead.
• Engage with business and technical stakeholders to gather requirements in coordination with the Data Layer Lead.
• Lead Agile ceremonies, including sprint planning, backlog refinement, and review sessions to support continuous delivery.
• Track progress against delivery plans and milestones, ensuring work remains on schedule.
• Provide regular reporting on progress, risks, dependencies, and performance metrics in alignment with the Data Layer Lead.
• Identify and manage risks, issues, and dependencies, ensuring timely mitigation and escalation as required.
• Ensure deliverables meet defined acceptance criteria and technical requirements.

b.      Cloud, DevOps & CI/CD Enablement

• Collaborate with the engineering team, in alignment with the Data Layer Lead, to support the design and implementation of CI/CD pipelines.
• Ensure deployment processes are efficient, repeatable, and aligned with DevSecOps practices.
• Support the implementation and use of AWS services (e.g., Glue, S3, Lambda, Athena, API Gateway) in alignment with the Data Layer Lead.
• Monitor pipeline performance and identify opportunities for automation and optimization.
• Promote best practices in cloud architecture, infrastructure as code, and environment management
• Ensure alignment with security and compliance requirements as directed by the Data Layer Lead.
• Support troubleshooting of pipeline and deployment issues, ensuring resolution and documentation.

c.       Technical Oversight & Data Engineering Support

• Work closely with data engineers, in alignment with the Data Layer Lead, to support the design and implementation of data pipelines, ETL processes, and APIs.
• Translate requirements into clear technical tasks and acceptance criteria for engineering teams.
• Review and validate technical solutions to ensure alignment with architecture, scalability, and performance requirements.
• Maintain a working understanding of data models, data flows, and system integrations across the platform.
• Support implementation of data governance practices including data quality, security, and access controls.
• Participate in technical discussions to support decision-making and alignment with platform standards.
• Assist in troubleshooting data and integration issues, ensuring root causes are identified and addressed.
• Ensure documentation of architecture, pipelines, APIs, and processes is maintained and up to date, including the creation of onboarding guides and usage documentation