Data Product Owner (Full Time)

We are looking for a Data Product Owner with a strong foundation as a data engineer, ideally with experience leading or supporting data pipeline migration initiatives. This role will be accountable for how existing data product workstreams are owned, developed and delivered, with the ability to quickly ramp up and assume ownership with minimal onboarding time.

The successful candidate will leverage their technical background to effectively partner with engineering teams from day one, serving as the connective layer between engineers, analysts and management.

The ideal candidate has recently transitioned from a data engineering role into product management, or is a highly technical data engineer looking to make that move. This Data Product Owner would translate business priorities into technical requirements and technical realities into business terms, working independently to drive priorities and manage cross-functional initiatives with minimal oversight.

Responsibilities:

• Own existing data product workstreams end-to-end, ramping up quickly and partnering with engineering teams from day one.
• Lead or support data pipeline migration initiatives, including planning, sequencing and coordinating cutover with engineering.
• Serve as the primary bridge between engineers, analysts and management, translating technical work into business terms and business priorities into technical requirements.
• Work in an agile environment, continuously reviewing business needs, prioritizing and maintaining the backlog, refining roadmaps, planning sprints and identifying opportunities and risks.
• Drive priorities and manage cross-functional initiatives independently, with minimal oversight.
• Partner with engineering leaders to balance the delivery of product features against platform foundational capabilities that drive scalability and resiliency.
• Build a culture of learning, knowledge sharing and high performance within the cross-functional team.
• Advocate for the highest standards of technical and operational excellence.

Requirements:

• Understanding SQL is a must.
• Python and R knowledge are a plus.
• Hands-on experience with the following tech stacks: Microsoft SQL Server, Aurora MySQL, Azure cloud (ADF), SQL Job Agents, SSIS, and AWS Cloud.
• Strong foundation as a data engineer, ideally with experience leading or supporting data pipeline migration initiatives.
• Recently transitioned from a data engineering role into product management, or a highly technical data engineer looking to make that move.
• Excellent communication and stakeholder management skills; comfortable serving as the bridge between engineers, analysts and management.
• Comfortable working independently, driving priorities and managing cross-functional initiatives with minimal oversight.
• A team player and self-starter.

Interview Process: 2 EXL team rounds + 2 client round interviews