BI Data Engineer

Description

The company is a Belgian tech firm (the company Belgium) with 600+ people, mainly working on international projects for the European Institutions, with over 8,900 staff across Europe.

The role is a BI data engineering position on large-scale projects that affect many citizens, within a team that values ideas and growth.

Responsibilities

• Build and run an open-source Data Lakehouse and modern BI data platforms.
• Design BI architectures across cloud, on-premises and hybrid setups, covering security, governance and data residency compliance.
• Create scalable ETL/ELT pipelines and orchestration workflows, including data contracts and schema evolution.
• Move legacy data flows onto modern platforms and build dependable pipelines for structured and unstructured data.
• Design data models, including dimensional models, for reporting, analytics and business needs.
• Develop BI and analytics solutions such as dashboards, KPIs, reports and self-service BI capabilities.
• Set up data quality, observability and monitoring covering lineage, freshness, SLAs and SLOs.
• Deploy and manage BI platforms with Infrastructure as Code, version control, CI/CD and environment management.
• Write and maintain technical documentation: data dictionaries, lineage, architecture specifications and operational runbooks.
• Enable self-service BI by providing curated datasets, certified reports, and guidance and support for business users.

Requirements

• Hold a university degree in Computer Science, Information Technology, Data Science, Artificial Intelligence or a related field, or have equivalent professional experience.
• Communicate well in English; knowledge of French is an advantage.
• Have a solid grasp of Data Lake and Data Lakehouse design patterns and hands-on work with tools such as Snowflake, Delta Lake and Airflow.
• Have strong experience with relational databases, especially PostgreSQL, including complex SQL and database design.
• Have hands-on experience using Python for data processing, including PySpark.
• Know BI and analytics tools such as Power BI, Tableau or Apache Superset for enterprise reporting and self-service analytics.
• Know ETL/ELT technologies such as dbt for building and managing enterprise data pipelines.
• Know cloud-based BI and data architectures, including platforms such as Snowflake and Databricks.
• Have experience with data quality management: validation rules, continuous monitoring and resolving issues across pipelines.
• Know data governance, cataloguing and data observability practices, including lineage, freshness monitoring and anomaly detection.

Conditions

Hybrid working model.

Equal opportunity policy: candidates are considered without regard to protected characteristics.

Submit your CV in English through the Apply button; applications are treated as strictly confidential.

Benefits

• Work in a modern environment.
• Competitive compensation and benefits package.
• Hospitalization plan.
• Meal allowance.
• Mobility budget or commuting allowance, where applicable.
• On-site well-being activities.
• Continuous learning, including unlimited access to Udemy for Business and ad-hoc training.
• Personalised development plan for career growth.