Senior Analytics Engineer: Build KPI Data Products in Databricks

team.blue; Gent; Sur place; EUR 80 000 - 110 000; Plein temps

Résumé du poste

team.blue seeks an experienced Analytics Engineer to join the AI & Data function. You’ll transform raw data into trusted datasets, building KPIs and semantic models feeding dashboards and reports.

You’ll work across marketing, product usage, customer care, revenue, and more, partnering with stakeholders to define KPI concepts and ensure data quality as you deliver analytics-ready products.

Qualifications

• 5+ years in analytics/data eng
• Hands-on with dbt core/cloud
• Experience on Databricks or similar
• Understanding of dimensional modelling/data warehousing
• Strong SQL with advanced transforms
• Autonomous across multiple domains with limited docs
• Analytical mindset to validate data end-to-end
• Excellent stakeholder communication
• Experience across marketing/product analytics domains

Responsabilités

• Design and build dbt models on Databricks to produce analytics-ready datasets
• Define KPI logic with stakeholders and ensure consistency
• Maintain semantic/presentation layer, with reliable data products
• Apply software engineering practices: version control, testing, CI/CD, documentation
• Onboard new data domains independently and model them
• Engage partners to validate assumptions and KPI definitions
• Collaborate with data engineers and analysts to meet reporting needs
• Contribute to data governance and model cataloguing
• Support expansion to new brands and domains over time

Connaissances

5+ years of experience in analytics

Autonomous work style

Analytical mindset

Excellent communication

Outils

dbt Core

Databricks

Snowflake

BigQuery

Looker/Tableau/Power BI

Python

Description du poste

team.blue seeks an experienced Analytics Engineer to join the AI & Data function. You’ll transform raw data into trusted datasets, building KPIs and semantic models feeding dashboards and reports.

You’ll work across marketing, product usage, customer care, revenue, and more, partnering with stakeholders to define KPI concepts and ensure data quality as you deliver analytics-ready products.