Analytics Engineer

This is a fully remote position, open to applicants in Belgium.

📋 Description

• Design and create robust dbt models on Databricks that transform raw, ingested data into clean, conformed, and analytics-ready datasets.

• Collaborate with business and analytics stakeholders to define and implement KPI logic, ensuring consistent definitions across various domains.

• Maintain and enhance the semantic/presentation layer, ensuring that data products are reliable, tested, documented, and high-performing.

• Utilize software engineering best practices for analytics code, including version control, testing, CI/CD, and thorough documentation.

• Independently onboard new data domains (such as marketing attribution, product usage, customer care, and subscription data) with minimal guidance—exploring the data, understanding its structure and meaning, and determining the best modeling approach.

• Actively engage with business partners and domain owners to grasp context, validate assumptions, and reach alignment on KPI definitions.

• Detect data quality issues early and collaborate with the Data Management team to address them at the source.

• Serve as a liaison between data engineers and analysts, translating analytical needs into engineering tasks and communicating data realities back to the business.

• Collaborate with the Analytics team to ensure the presentation layer meets reporting and self-service requirements.

• Contribute to data governance by establishing naming conventions, documenting lineage, and cataloguing models.

• Assist the broader team in expanding analytics coverage to new brands and domains over time.

⛳️ Requirements

• Over 5 years of experience in analytics engineering, data engineering, or a closely related data role.

• Strong, hands-on expertise with dbt (dbt Core or dbt Cloud) — this is a fundamental requirement.

• Experience working with Databricks (or a comparable cloud data platform such as Snowflake or BigQuery).

• Solid knowledge of dimensional modeling, data vault, or similar data warehousing methodologies.

• Exceptional SQL skills: capable of handling complex transformations, window functions, and query optimization.

• Proven capability to work independently across multiple data domains simultaneously, navigating unfamiliar data with limited documentation.

• Strong analytical abilities: adept at critically examining data, identifying anomalies, and validating logic from start to finish.

• Excellent communication skills — comfortable engaging directly with business stakeholders to gather requirements and explain data concepts.

• Experience working across various data domains (e.g., marketing, product analytics, customer care, and financial/subscription data).

🏝️ Benefits

• Options for remote work

• Flexible working hours

• Opportunities for professional development