Data Platform Development: Building and improving the data infrastructure, including developing pipelines, integrating new sources, and analytical data modeling within the Data Warehouse.
Reporting & Governance: Creating reporting systems and analytical datasets, developing dashboards, defining/documenting business KPIs, and contributing to data organization and governance.
Business Analytics: Conducting ad-hoc analyses, scenario simulations (pricing, occupancy, etc.), and developing analytical tools to optimize strategic decision-making.

Experience: 5+ years in roles related to Analytics Engineering, Data Analytics, or Data Engineering.
Education: Degree in Engineering, Mathematics, Statistics, Data Science, Computer Science, or a similar field.
Advanced mastery of SQL and experience using Python for data analysis and transformation.
Hands-on experience with Data Warehouses (Redshift, Snowflake, or BigQuery) and analytical data modeling.
Proven track record building data pipelines and integrating diverse information sources.
Proficiency with BI tools (Metabase, Looker, Tableau, or Power BI) for dashboarding.
Knowledge of Cloud environments, specifically AWS (S3, Lambda Functions, CloudWatch).
A methodical and structured mindset with analytical curiosity.
Ability to translate business problems into data-driven solutions and thrive in agile, small-team environments.
Nice to have: Experience with DBT, Airflow, or Prefect, as well as knowledge of applied statistics or predictive modeling.

Dynamic Environment: Join a young, fast-growing, multidisciplinary team oriented toward product excellence.
Flexibility: Flexible working hours (Start: 08:00–10:00 / End: 17:00–19:00).
Hybrid Model: 4 days in-office / 1 day remote.
Holidays: 29 working days of vacation per year.
Perks & Wellness: Subsidized catering/meals, plus free coffee, fruit, and snacks in the office.
Subsidized private medical insurance.
Travel Benefits: 60% discounts on stays across our portfolio of establishments.

Data Analytics Engineer

Key skills