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- Tasks: Own and optimise the analytics data layer for multiple iGaming brands.
- Company: Dynamic iGaming company focused on data-driven decision-making.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and problem-solving.
- Why this job: Make a real impact by improving data structures and driving insights across the business.
- Qualifications: 5-8 years in data roles with strong SQL and data modelling skills.
The predicted salary is between 60000 - 80000 ÂŁ per year.
We are looking for a Senior Data Warehouse Analyst to take ownership of our analytics data layer across multiple iGaming brands. This role sits at the core of BI & Analytics - ensuring that our data is structured correctly, consistently defined, and reliable for all downstream reporting and decision-making. You will work across raw data, transformation logic, and reporting structures to ensure we have a clear and trusted “single source of truth” - while also identifying and fixing data issues at their root cause. This is a hands-on role for someone who thinks beyond queries and understands how data should be designed, not just consumed.
Key Responsibilities:
- Data Warehouse Ownership & Structure
- Own and evolve the structure of the analytics data layer (tables, views, aggregates)
- Ensure consistent definitions across key KPIs (GGR, NGR, deposits, bonus cost, player metrics)
- Eliminate duplication of logic and conflicting calculations across tables and reports
- Design and maintain scalable data structures to support analytics and reporting needs
- Work with backend/data teams to define how new data should be ingested and structured
- Data Quality & Reliability
- Ensure accuracy, completeness, and consistency of data across all reporting layers
- Identify discrepancies across datasets and trace issues back to source, transformation, or logic
- Design and implement structured QA and reconciliation processes
- Reduce recurring issues by improving underlying data structure rather than patching outputs
- Data Processing & Optimisation
- Work with stored procedures and transformation logic to maintain and improve data pipelines
- Optimise queries, aggregations, and table design for performance and scalability
- Implement efficient data strategies (pre-aggregation, incremental logic, partitioning where applicable)
- Ensure data is performant and usable across BI tools and analytics workflows
- Issue Investigation & Cross-Team Collaboration
- Act as the main point of contact for data issues between BI and backend/IT teams
- Translate business/data issues into clear technical requirements
- Drive resolution of issues end-to-end - from identification to validation
- Communicate clearly when data issues impact reporting or decision-making
- Data Enablement & Process Improvement
- Document data structures, logic, and KPI definitions
- Create clarity around how data is built and used across the business
- Introduce repeatable processes to reduce manual work and firefighting
- Support the analytics team with SQL-based analysis when needed
What We’re Looking For:
Experience
- 5-8+ years in data, BI, or data warehouse roles
- Strong experience working with transactional datasets (e.g. bets, payments, events, financial data)
- Experience in iGaming or similar high-volume data environments preferred
- Experience working close to data modelling or warehouse layers (not just reporting)
Technical Skills
- Advanced SQL (joins, aggregations, window functions, performance optimisation)
- Experience working with stored procedures and transformation logic
- Strong understanding of:
- data grain and aggregation layers
- KPI consistency and single source of truth principles
- designing reporting tables and datasets
- Experience improving data performance (large tables, optimisation, query efficiency)
Data Thinking
- Thinks in terms of data structures and flow, not just queries
- Able to challenge inconsistent logic and improve data design
- Understands trade-offs between ideal architecture and business speed
- Comfortable working in imperfect environments and improving them over time
Collaboration & Ownership
- Strong communicator with technical and non-technical teams
- Able to clearly explain issues, root causes, and proposed solutions
- High ownership mindset - identifies problems and drives them to resolution
- Comfortable working independently in a fast-paced environment
What Success Looks Like (3-6 months):
- Clear and consistent KPI definitions across all key business areas
- Improved trust in data across BI, CRM, marketing, and product teams
- Reduction in recurring data issues and discrepancies
- More structured, scalable data layer supporting analytics and reporting
- Faster turnaround on data-related questions and issue resolution
Why Join Us:
This is an opportunity to take ownership of a critical layer of the business - the data that powers decision-making across multiple brands. You will have direct impact on how data is structured, trusted, and used, working closely with analytics, marketing, product, and engineering teams. If you enjoy solving real data problems, improving systems over time, and building clarity out of complexity - this is a strong opportunity to do it.
Senior Data Warehouse Analyst in England employer: sixvalues
Contact Detail:
sixvalues Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Warehouse Analyst in England
✨Tip Number 1
Network like a pro! Reach out to your connections in the iGaming industry and let them know you're on the hunt for a Senior Data Warehouse Analyst role. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies that highlight your experience with data structures, SQL optimisation, and problem-solving in data environments. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Ace the interview by being ready to discuss real-world scenarios. Think about how you've tackled data quality issues or improved data performance in past roles. Use these examples to demonstrate your hands-on experience and ownership mindset.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team and taking ownership of our analytics data layer.
We think you need these skills to ace Senior Data Warehouse Analyst in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Data Warehouse Analyst. Highlight your experience with data structures, KPIs, and any relevant iGaming background. We want to see how your skills align with our needs!
Showcase Your Technical Skills: Don’t hold back on your SQL prowess! Detail your experience with stored procedures, performance optimisation, and data modelling. We’re looking for someone who can dive deep into data, so let us know what you’ve got!
Demonstrate Problem-Solving Abilities: Share examples of how you've tackled data issues in the past. We love candidates who can identify root causes and implement long-term solutions. Show us your analytical thinking and ownership mindset!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Let’s get started on this journey together!
How to prepare for a job interview at sixvalues
✨Know Your Data Inside Out
Before the interview, dive deep into your understanding of data structures and flow. Be ready to discuss how you’ve designed and optimised data layers in previous roles, especially focusing on KPIs and ensuring a single source of truth.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've identified and resolved data discrepancies in the past. Highlight your approach to root cause analysis and how you’ve implemented structured QA processes to improve data reliability.
✨Communicate Clearly and Confidently
Practice explaining complex data issues in simple terms. You’ll need to demonstrate your ability to communicate effectively with both technical and non-technical teams, so think of scenarios where you’ve successfully bridged that gap.
✨Be Ready to Discuss Collaboration
Think about times when you’ve worked cross-functionally with BI, backend, or IT teams. Be prepared to share how you’ve driven resolutions from identification to validation, showcasing your ownership mindset and collaborative spirit.