At a Glance
- Tasks: Own the data layer, ensuring accurate data flows for top brands in gaming.
- Company: GEEIQ, a fast-growing startup revolutionising marketing analytics in virtual worlds.
- Benefits: Flexible hybrid work, collaborative culture, and opportunities for career growth.
- Why this job: Be at the forefront of gaming and marketing, working with iconic brands like Gucci and Porsche.
- Qualifications: 2-4 years in data operations, fluent in SQL/NoSQL, and an AI-first mindset.
The predicted salary is between 63000 - 77000 £ per year.
GEEIQ is a Series A startup building the analytics engine for marketing in virtual worlds, helping global brands like Gucci, L'Oréal, and Porsche measure ROI across platforms like Roblox and Fortnite.
You will own the operational data layer for GEEIQ, ensuring accurate and trustworthy data flows between virtual worlds and global brands. This hands-on role involves pulling, validating, and importing data using SQL and NoSQL databases. You'll work AI-first to unblock the team, maintaining the reliable backbone that powers our product and client services.
Location: London, UK
Why this role is remarkable:
- Sit at the intersection of gaming and big-brand marketing, working with high-profile data from environments like Fortnite and Roblox for clients like Walmart and Porsche.
- Join a high-growth Series A startup with a 52 eNPS score - nearly double the industry average - reflecting a culture that genuinely values collaboration, innovation, and flexible hybrid work.
- Be genuinely indispensable in a role with a non-engineering growth path, moving into owning data quality functions and attribution research as the company defines a new marketing frontier.
What You Will Do:
- Own data access across the product lifecycle by pulling, shaping, and delivering actionable data in the format needed by product, sales, and client service teams.
- Validate and quality-check platform data to identify anomalies and spot trends, ensuring every number provided to world-class brands is accurate and trustworthy.
- Partner with data engineers to manage routine ingestion tasks and use AI tools like Cursor and Claude to rapidly translate business logic into complex database queries.
The ideal candidate possesses:
- 2-4 years of experience in data operations, BI, or revenue ops, with a service-oriented mindset and a pride in being the reliable go-to for data needs.
- Fluency in SQL and NoSQL (MongoDB/Elasticsearch), including the ability to read nested JSON structures and audit AI-generated code for safety and optimization.
- A sophisticated AI-first approach, with experience prototyping or building with tools like Claude Code, Cursor, or agentic workflows rather than just using basic chat interfaces.
Data Operations Specialist at GEEIQ in London employer: Jack & Jill
At Jack & Jill, we pride ourselves on being an exceptional employer that fosters a dynamic and innovative work culture. Our team enjoys a range of benefits including flexible working arrangements, professional development opportunities, and a collaborative environment that encourages creativity and growth. Located in a vibrant area, we offer unique advantages such as access to cutting-edge technology and the chance to work with industry leaders in AI-driven marketing strategies.
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We think this is how you could land Data Operations Specialist at GEEIQ in London
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We think you need these skills to ace Data Operations Specialist at GEEIQ in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
