Senior Analytics Engineer

Навыки

• Airflow
• BI-инструменты
• BigQuery
• CI/CD
• Коммуникация
• CRM-системы
• Дашборды и витрины

О компании и продукте

• We are a global technology group, dedicated to building the future of entertainment and fan-centric experiences. With commercial markets in Brazil, Belgium, Poland, Romania, Greece and Serbia, and a network of offices across Spain, Croatia, Malta, Gibraltar, the Netherlands and the UK, we are a truly international organization. Our purpose at Super has evolved from sports and betting into creating the platform that stretches into the wider world of technology-driven entertainment. With a growing and diverse team of more than 5,000 people, we create immersive, responsible, and personalised experiences for millions of customers worldwide.
• Everything we do at Super is rooted in doing what is right: for customers, for each other, and for our long-term vision. Our Culture Manifesto is our North Star. It captures our purpose, mission, and the six core beliefs that shape how we think, make decisions, and act every day. Want to explore our culture in more detail? Visit our careers page: super.xyz/careers
• Super is committed to the highest standards of compliance, safety, and responsibility. As such, we are active members of the International Betting Integrity Association (IBIA) and the European Gaming & Betting Association (EGBA).
• At Super, we operate as a high-performing team. We hire and grow talent based on ability and potential, regardless of background and identity because we know diverse perspectives, drive better performance.

Задачи

• You will be joining a mature and growing community of 40+ data engineers and analytics engineers who are shaping one of the most advanced data ecosystems in the industry
• What the role involves
• Design and build curated analytical datasets, metric implementations, and semantic models that enable consistent self-service analytics across the company
• Partner closely with product, data scientists, and business stakeholders to clarify requirements and translate them into reliable data models and reporting-ready outputs
• Build and own production dashboards (Tableau) on top of curated datasets and metric definitions, ensuring correctness, performance, and a consistent single source of truth
• Contribute to data quality, observability, lineage, and documentation practices to increase trust and reduce firefighting
• Promote reuse over reinvention — identify ad-hoc logic in reporting views or custom SQL and refactor it into curated, high-quality models that multiple teams can rely on
• Raise the engineering bar through reviews, testing, automation, and pragmatic architectural improvements
• Drive self-service adoption by creating foundations that allow analysts and business users to explore data safely and independently
• Work embedded within Data Engineering squads, collaborating daily with data engineers and analysts on shared foundations and end-to-end delivery

Требования

• Strong SQL skills and proven experience building analytical datasets and metrics in a modern data warehouse (Snowflake preferred
• BigQuery, Redshift, and similar also valuable)
• Solid understanding of data warehouse modelling and best practices — dimensional modelling, fact/dimension design, grains, slowly changing dimensions, and semantic consistency
• Experience working with reporting and BI tools (Tableau preferred), including understanding how data sources, extracts, and dashboard logic impact correctness, performance, and trust
• A production mindset: care for reliability, maintainability, documentation, and operational ownership — not just creating a dataset once
• Strong ownership and collaboration skills — able to drive clarity in ambiguous problem spaces and partner effectively with both technical and non-technical teams
• Excellent communication skills with a pragmatic, problem-solving approach
• Work hands-on with data warehouse modelling to turn evolving product and business needs into scalable, reusable data structures

Будет плюсом

• Experience with orchestration and workflow tooling (Airflow or similar)
• Experience with data cataloguing, lineage, and governance tooling (e.g., DataHub)
• Background in product-led, experimentation-driven, or high-growth environments where definitions evolve quickly
• Experience supporting downstream operational consumers (e.g., CRM/audience platforms) or ML/feature engineering use cases
• Familiarity with streaming/event-heavy ecosystems (Kafka or similar)

Условия

• Medical / Health Insurance
• Open Annual Leave
• Employee Assistance Programme
• Training & Learning Development
• Additional benefits vary by country and will be shared during the hiring process

Паспорт вакансии

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