Senior Analytics Engineer

We are on a mission to pioneer the world’s next era of play. As we grow across Europe and Latin America, we’re building The Playstack - the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world!

From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day. At Super Technologies, data is a strategic enabler of decision-making, experimentation, and performance measurement. Our Analytics Platform team builds the foundations that make data reliable, accessible, and actionable, partnering with product, commercial, and engineering teams to measure what matters.

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. Work hands-on with data warehouse modelling to turn evolving product and business needs into scalable, reusable data structures.

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. Apply engineering rigour to analytics — treat semantics as code, utilising version control, testing, automation, and CI/CD practices to manage the lifecycle of business logic.

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.

What We Are Looking For

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.

Nice To Have

Experience with orchestration and workflow tooling (Airflow or similar). , DataHub). Background in product-led, experimentation-driven, or high-growth environments where definitions evolve quickly.

, CRM/audience platforms) or ML/feature engineering use cases. Familiarity with streaming/event-heavy ecosystems (Kafka or similar).

What We Offer

Medical / Health Insurance Open Annual Leave Employee Assistance Programme Training Learning Development Additional

Benefits

vary by country and