We are seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data pipelines and enterprise-level data architecture. This role is focused on technical leadership without people management, where you will drive the architecture and delivery of high-quality data solutions supporting analytics, reporting, and AI/ML initiatives. The ideal candidate is hands-on, analytical, and experienced in building robust data platforms across cloud and on-prem environments. Key Responsibilities - Design and implement scalable, high-performance data pipelines for structured and unstructured data - Build and maintain enterprise-grade data architecture across cloud and on-prem environments (AWS, Azure, or GCP) - Define and implement data modeling strategies (data warehouses, data lakes, real-time streaming) - Collaborate with business stakeholders to translate requirements into technical solutions - Ensure data quality, governance, security, and compliance across all data assets - Perform complex data analysis and support reporting and analytics initiatives - Evaluate and recommend modern tools, frameworks, and best practices in data engineering - Integrate data from multiple sources and optimize data performance - Provide technical direction and architectural guidance across data projects

• 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 • 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 • 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 • 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 • 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

• Design, build, and maintain scalable data platforms and solutions tailored to business needs • Collaborate with stakeholders across teams to understand requirements and deliver impactful data initiatives • Optimize and monitor data workflows to ensure performance, scalability, and reliability • Stay current with the latest trends in data technologies and apply innovative solutions to complex challenges

• Design, build, and maintain scalable data platforms and solutions tailored to business needs • Collaborate with stakeholders across teams to understand requirements and deliver impactful data initiatives • Optimize and monitor data workflows to ensure performance, scalability, and reliability • Stay ahead with the latest trends in data technologies, applying innovative solutions to complex challenges