Analytics Engineer

2d2 days ago

Inner Circle

Amsterdam, NL · Full-time · €55,000 – €75,000

About this role

Every match, every date, every Full Circle starts with data. As Analytics Engineer you own the data stack end-to-end, building the infrastructure that powers product, marketing and commercial decisions at Inner Circle.

You work closely with the data lead on priorities while driving execution across pipelines, models, orchestration and observability. The stack grows smoothly with new markets and data sources while infrastructure costs stay under control.

You ensure the data the whole company relies on remains correct, consistent and up to date. Quality issues are caught before they reach reports, metrics are defined uniformly, and tables are structured for easy self-service access.

You keep the data stack documented so anyone, including AI tools querying Snowflake, can use it confidently. You partner with product, marketing, finance and operations teams, delivering answers and raising the bar on quality, efficiency and shared definitions.

Requirements

Strong experience with data warehousing platforms, particularly Snowflake
Hands-on experience with dbt for data modelling and transformation
Proficiency with data orchestration tools such as Dagster or similar
Strong SQL skills and experience designing data models for analytics workflows
Experience with Python for data engineering tasks
Track record of building reliable, well-documented data pipelines in production
Ability to translate business questions into data structures and models
Self-starter who takes ownership of projects from start to finish

Responsibilities

Own the data infrastructure end-to-end including pipelines, models, orchestration and observability
Monitor infrastructure costs and make technical decisions in collaboration with the data lead
Ensure data is correct, consistent and up to date so quality issues never reach reports or decisions
Maintain clear documentation so tables, models and fields are self-explanatory and data flows stay current
Partner with product, marketing, finance and operations teams to deliver answers through self-service or direct support
Continuously improve quality, efficiency and clarity while contributing to shared data definitions