The Role
As a Senior Analytics Engineer, you will influence data architecture, establish standards, mentor engineers, and drive analytics engineering capabilities across the organization.
Summary Generated by Built In
Veo is a global leader in AI-based sports camera technology. Our innovative, fully automatic camera solution enables sports teams to record matches and training sessions without a camera operator. We’re democratizing the world of sports by granting video analysis for teams on all levels—a privilege that used to be only for the few. More than 40,000 clubs in 90+ countries record their games every week.
Growing as fast as we do in Veo means that every day is different, exciting, and challenging, both on the front line and in the back office.
But that’s not the most remarkable thing about us.
The coolest thing is our people. We’ve attracted some of the brightest minds in the industry. They are the reason we can create a great product and do it while enjoying ourselves.
About the Role
As a Senior Analytics Engineer at Veo, you'll be a key technical voice influencing the strategic direction of our analytics engineering practice. You'll work within our data team (1 analyst, three analytics engineers, and 1 data engineer) and with six embedded analysts across the organization, establishing architectural patterns, shaping technical standards, and building the scalable foundations that enable reliable analytics company-wide.
You'll bring your deep technical expertise and strategic thinking to influence how Veo approaches data modeling, metrics definitions, and analytics engineering practices. You'll establish the frameworks and standards that others adopt, mentor the team toward technical excellence, and demonstrate the architectural approaches that enable Veo's data platform to scale with the business.
What will you do:
- Influence foundational data architecture strategy by designing patterns and establishing standards that shape how the organization builds scalable, reliable, and maintainable analytical data products
- Shape analytics engineering practice across the data team and embedded analysts through establishing best practices, driving technical excellence in code reviews, and building frameworks that enable consistent, high-quality data modeling
- Design and champion the metrics layer and semantic definitions, establishing patterns for consistent business logic and trusted metrics that become organizational standards across all analytical work
- Mentor and develop analytics engineering talent, working closely with 3 analytics engineers and spreading technical excellence to embedded analysts through knowledge sharing, hands-on guidance, and establishing development frameworks
- Drive continuous improvement of analytics engineering capabilities by demonstrating value through automation, testing frameworks, and tooling decisions that reduce complexity while increasing reliability and speed
What could you bring:
- Proven experience in a similar role at Senior Analytics Engineer level or above, with a track record of influencing data architecture decisions and establishing technical standards across organizations
- Expert-level proficiency in SQL, dbt, and data modeling with a deep understanding of dimensional modeling, design patterns for analytics at scale, and modern data warehouse architecture (ideally BigQuery)
- Strong experience with analytics engineering best practices, including CI/CD, version control, automated testing, data quality frameworks, and documentation standards
- Proven ability to mentor and develop technical talent with experience elevating team capabilities through knowledge sharing and establishing development frameworks
- Strategic mindset with ability to balance technical excellence with business pragmatism, connecting data architecture decisions to business outcomes and demonstrating value to drive adoption
What we look for in your application:
Demonstrated ability to influence technical standards and drive adoption through value. We'd love to hear examples of data models, metrics layers, or analytics engineering practices you've established—how did you design them, why did you make those architectural choices, how did you drive adoption across teams, and what would you do differently?
Our Copenhagen office mirrors our innovative technology – with an indoor ball court, rooftop terrace, and well-equipped gym. We have created a facility that supports connecting disciplines across the business, facilitates creative thinking, and gives the space to engage with colleagues, our global partners, and the entire Veo community.
Values we hold at Veo:
Dare - We take initiative, stay curious, and challenge the status quo in our work.
Own it - We drive impact by identifying opportunities, taking responsibility, and confidently executing.
Level up - We embrace growth, continuously learning and shaping our skills.
Play as a team - We collaborate across a diverse organization, leveraging shared insights for stronger
outcomes.
Customer Centric - We deliver value by having close partnerships and a deep understanding of our customers (internally and externally)
We value diversity and inclusion and welcome applicants from all backgrounds, even if your experience doesn’t completely match every qualification listed. What matters most is your creativity, potential, and ability to make meaningful contributions.
Top Skills
BigQuery
Dbt
SQL
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The Company
What We Do
Record your sport - without a camera operator.
Veo lets you record your sports match without a camera operator. Automatic recording and video-editing enables coaches and players to watch and share their sport.
Veo is founded in 2015 in Copenhagen. Our vision is to democratise the video broadcasting and analytics that today only are available for the professional teams.
Veo is offered for clubs, players, coaches, scouts, families and fans to give access to quality video. The videos give automised panoramic, ball detector and player detector views. The platform contains analytical and sharing features enabling all users to access and utilise the content.
