Senior dbt Analytics Engineer – PySpark & Apache Iceberg – Brussels

All European Careers BENELUX; Brussel Hoofdstad; Hybrid; EUR 90,000 - 120,000; Full time

Job summary

All European Careers BENELUX in Brussels, Belgium is seeking a Senior Analytics Engineer to design and optimize scalable data transformation pipelines using dbt and PySpark. You will modernize legacy workflows, ensure data quality, and support pipelines across enterprise analytics environments.

The role requires 6+ years of IT experience, strong SQL, and hands-on dbt Core, PySpark, and Iceberg expertise. You will collaborate with data engineers, analysts, and business stakeholders in a hybrid

Qualifications

• 6+ years of IT experience
• Hands-on with dbt Core in production
• Strong analytics engineering, data modelling and modular dbt architectures
• Advanced SQL skills with complex transformations and incremental processing
• Experience with PySpark and Apache Spark
• Experience with Apache Iceberg including schema/partition evolution and time travel
• Data quality, automated testing and validation during migrations
• Familiarity with Git, CI/CD pipelines and code reviews

Responsibilities

• Design, develop and maintain scalable data transformation pipelines using dbt and PySpark
• Optimize dbt project performance, SQL transformations and incremental processing
• Develop and maintain data quality checks, automated regression tests and pipeline validation
• Design modular dbt models with staging, intermediate and marts layers
• Work with Apache Iceberg tables including schema evolution and time travel
• Translate business requirements and legacy logic into reliable data transformations
• Support migration and reconciliation activities ensuring functional equivalence between pipelines
• Establish dbt development best practices and maintain technical documentation

Skills

dbt

SQL

PySpark

Apache Iceberg

Data quality

CI/CD

Dagster

Data modeling

Stakeholder collaboration

Education

Bachelor's or Master's in IT/CS

Tools

Apache Spark

Git

Dagster

CI/CD tooling

Job description

We are looking for a Senior Analytics Engineer in Brussels, Belgium, with strong expertise in dbt, SQL, PySpark and Apache Iceberg.

You will design and optimize scalable data transformation pipelines, modernize legacy data processing workflows and ensure data quality across enterprise analytics environments.

Hybrid Brussels – 6+ years of IT experience

Tasks and Responsibilities

• Design, develop and maintain scalable data transformation pipelines using dbt and PySpark;
• Optimize dbt project performance, SQL transformations and incremental data processing;
• Develop and maintain data quality checks, automated regression tests and pipeline validation procedures;
• Design modular dbt models using staging, intermediate and marts layers, reusable macros and established analytics engineering practices;
• Work with Apache Iceberg tables, including schema evolution, partition evolution and snapshot management;
• Translate business requirements and legacy processing logic into reliable, production-ready data transformations;
• Support migration and reconciliation activities, ensuring functional equivalence between legacy and modern data pipelines;
• Establish dbt development best practices, maintain technical documentation and collaborate with data engineering and business teams.

Profile

• Bachelor's or Master's degree and 6+ years of IT experience;
• Proven hands-on experience with dbt, preferably dbt Core, including production development, testing, documentation and maintenance;
• Strong knowledge of analytics engineering, modern data modelling and modular dbt architectures;
• Advanced SQL skills, including complex transformations, query optimization and incremental processing;
• Practical experience with PySpark and Apache Spark, including distributed processing, partitioning and performance optimization;
• Proven experience with Apache Iceberg, including schema evolution, partition evolution, snapshot management and time travel;
• Strong understanding of data quality, reconciliation, automated testing and validation, particularly during legacy system migrations;
• Experience with Git, CI/CD pipelines, code reviews and automated deployment practices;
• Familiarity with workflow orchestration and scheduling tools, such as Dagster, for dbt and Spark workloads;
• Ability to document technical solutions and collaborate with data engineers, analysts, business stakeholders and platform teams.

Experience with SAS-based ETL and migration from SAS to dbt would be a strong advantage. Knowledge of Spark job optimization and advanced Apache Iceberg internals, including compaction and transaction behavior, would also be beneficial.