Data Product Owner/Manager

As a Data Product Owner/Manager at BTSE, your main responsibilities include acting as the main liaison between business owners and the data team, gathering and analyzing business requirements, prioritizing the backlog of data requests, and ensuring effective communication among stakeholders. You will also collaborate closely with data analysts and scientists to translate business needs into precise technical specifications and track project progress to ensure timely delivery of data-driven solutions.

To qualify for the Data Product Owner/Manager position at BTSE, candidates should have a minimum of 3 years’ experience in product or project management, a strong understanding of data analysis and reporting, and excellent communication skills. Familiarity with Agile methodologies and the ability to manage multiple projects simultaneously will also enhance your candidacy, along with a background in fintech or data science which is considered a bonus.

The Data Product Owner/Manager at BTSE plays a crucial role in aligning data projects with business strategy by ensuring that data initiatives reflect business needs and drive value. By effectively gathering requirements, prioritizing strategic projects, and advocating for a data-driven culture, this role supports the overall ambition of BTSE to enhance its innovative technology and infrastructure offerings in the fintech space.

A successful Data Product Owner/Manager at BTSE is typically an organized and communicative individual who thrives in dynamic environments. This role requires someone who is proactive at problem-solving, can manage multiple tasks effectively, and is passionate about leveraging data to generate impactful business outcomes. A collaborative spirit and a knack for strategizing alongside teams are also vital for success.

Working as a Data Product Owner/Manager at BTSE comes with an attractive benefits package. This includes a competitive salary, comprehensive healthcare schemes for you and your dependants, and various opportunities for professional growth in a fast-paced environment. Additionally, BTSE values team building and offers many company events that foster a sense of community among employees.

In your answer, emphasize key projects you've managed, focusing on your role in bridging communication between technical and business teams. Highlight how your contributions led to improved efficiency or data-driven decisions.

Discuss your criteria for prioritization, such as aligning with business strategy, potential impact, and resource availability. Provide examples of how you've successfully managed competing requests in the past.

Elaborate on your approach to promoting data solutions, including sharing success stories, conducting training sessions, and providing actionable insights that demonstrate the benefits of data-driven strategies.

Explain your conflict resolution skills, emphasizing your ability to listen, mediate, and align stakeholder interests. Share a specific example where you successfully navigated differing opinions to reach a consensus.

Discuss your familiarity with Agile methodologies and how you apply them in managing data projects, including sprint planning, retrospectives, and maintaining a backlog. Share any tools you prefer to use, such as JIRA or Trello.

Prepare a specific example where an analysis you conducted led to a significant change or strategy implementation in your previous role. Make sure to quantify the impact when possible.

Detail your collaborative process, emphasizing clear communication, establishing shared goals, and regular check-ins. Illustrate with an example of a successful project that required teamwork across these functions.

Mention essential project management tools you have used and find effective, such as data visualization tools or analytics dashboards, along with any software that enhances collaboration within your team.

Discuss the key performance indicators (KPIs) you track to assess project impact, including time-to-delivery, user adoption rates, or business outcome improvements. Highlight the importance of post-implementation reviews.

Share specific challenges related to data projects, such as data quality issues or stakeholder alignment. Discuss your problem-solving approach and what you learned from those experiences.