Senior Business Intelligence Analyst
Tripledot Studios
| Company | Tripledot Studios |
| Category | Data & Analytics |
| Location | London |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 16 Jul 2026 |
| Last verified | 7 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
Who are we?
Tripledot Studios is one of the largest independent mobile games companies in the world.
We are a multi-award-winning organisation, with a global 2,500+ strong team across 12 studios.
Our expanded portfolio includes some of the biggest titles in mobile gaming, collectively reaching top chart positions around the world and engaging over 25 million daily active users.
Tripledot’s guiding principle is that when people love what they do, what they do will be loved by others.
We’re building a company we’re proud of. One filled with driven, incredibly smart and detail-orientated people, who LOVE making games.
Our ambition is to be the most successful games company in the world, and we’re just getting started. Role Overview
As a Senior BI Analyst on the Group AI team, you will play a key role in building the reporting and visualisation tools that turn our models into insight the wider business can act on. The Group AI team builds and maintains the predictive models used by every studio within Tripledot Group, and your role is to make sure the results of that work are surfaced clearly and effectively to the teams who depend on them. You'll work closely with our ML Engineers, Data Scientists, and Data Engineers.
You will own our Looker environment end to end — connecting new data sources, modelling a clean and reliable LookML semantic layer, and building the dashboards and self-serve tools that our UA analysts and marketing leadership rely on every day. Beyond building, you will bring a curious, analytical mind to our data, proactively uncovering opportunities that help improve our ML products.
This is a full-time, senior-level position with the opportunity to work with a talented and passionate team, contribute to the growth of our mobile gaming products, and make a significant impact within the company.
Key Responsibilities
Own our Looker environment end to end — connect new data sources, author and maintain the LookML semantic layer (views, explores, models and derived tables), and build the final dashboards, all independently.
Design and build self-serve tools and dashboards that empower UA analysts and marketing leadership across the Group's studios to answer their own questions and act on real-time insight into key metrics such as LTV, retention, monetisation and ROAS.
Conduct regular data quality checks and audits, and QA the reporting of key metrics — reconciling dashboards against the team's predictive model outputs and catching issues before they reach stakeholders.
Partner closely with stakeholders to understand what the business needs and wants — not just what they ask for — and translate those requirements into the right dashboards, metrics and visualisations.
Collaborate with cross-functional teams — including our ML Engineers, Data Scientists and Data Engineers, as well as product managers, UA analysts and marketing leadership across the studios — to identify reporting needs and implement effective solutions.
Write clear specifications for the data models you need our data engineering team to build upstream, using sound judgement on when a transformation belongs in LookML versus in the warehouse.
Required Skills, Knowledge and Expertise
Bachelor's degree in a relevant field (e.g., Computer Science, Mathematics, Statistics, or similar).
Proven experience as a BI Engineer, BI Analyst or similar role, preferably within the gaming industry.
Expert-level proficiency in Looker and LookML, with a demonstrated ability to work full-stack within Looker — connecting data sources, modelling the semantic layer, and building dashboards independently.
Experience with other BI and visualisation platforms (e.g., Tableau, Power BI).
Proficiency in SQL and experience working with large datasets.
Demonstrated experience building self-serve BI that empowers non-technical users, rather than only servicing one-off report requests