Senior dbt Analytics Engineer – PySpark

Il y a 4 heures
Arrondissement of BrusselsCapital, Brussels, Belgique All European Careers BENELUX Temps plein
pWe are looking for a bSenior Analytics Engineer /b in bBrussels, Belgium /b, with strong expertise in bdbt, SQL, PySpark and Apache Iceberg /b. /ppYou will design and optimize scalable data transformation pipelines, modernize legacy data processing workflows and ensure data quality across enterprise analytics environments. /ph3Hybrid Brussels – 6+ years of IT experience /h3h3Tasks and Responsibilities /h3ulliDesign, develop and maintain bscalable data transformation pipelines /b using dbt and PySpark; /liliOptimize bdbt project performance /b, SQL transformations and incremental data processing; /liliDevelop and maintain bdata quality checks, automated regression tests and pipeline validation procedures /b; /liliDesign modular dbt models using staging, intermediate and marts layers, reusable macros and established analytics engineering practices; /liliWork with bApache Iceberg tables /b, including schema evolution, partition evolution and snapshot management; /liliTranslate business requirements and legacy processing logic into reliable, production-ready data transformations; /liliSupport migration and reconciliation activities, ensuring functional equivalence between legacy and modern data pipelines; /liliEstablish dbt development best practices, maintain technical documentation and collaborate with data engineering and business teams. /li /ulh3Profile /h3ulliBachelor's or Master's degree and b6+ years of IT experience /b; /liliProven hands-on experience with bdbt /b, preferably dbt Core, including production development, testing, documentation and maintenance; /liliStrong knowledge of banalytics engineering, modern data modelling and modular dbt architectures /b; /liliAdvanced bSQL skills /b, including complex transformations, query optimization and incremental processing; /liliPractical experience with bPySpark and Apache Spark /b, including distributed processing, partitioning and performance optimization; /liliProven experience with bApache Iceberg /b, including schema evolution, partition evolution, snapshot management and time travel; /liliStrong understanding of bdata quality, reconciliation, automated testing and validation /b, particularly during legacy system migrations; /liliExperience with bGit, CI/CD pipelines, code reviews and automated deployment practices /b; /liliFamiliarity with bworkflow orchestration and scheduling tools /b, such as Dagster, for dbt and Spark workloads; /liliAbility to document technical solutions and collaborate with data engineers, analysts, business stakeholders and platform teams. /li /ulpExperience with bSAS-based ETL and migration from SAS to dbt /b would be a strong advantage. Knowledge of Spark job optimization and advanced Apache Iceberg internals, including compaction and transaction behavior, would also be beneficial. /p

  • Senior dbt Analytics Engineer – PySpark

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