Database Analytics Engineer

EUROPEAN DYNAMICS

. Design and develop scalable, reliable data transformation pipelines and workflows .

Posted 10/23/2026full-timeBrussels • BelgiumSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing scalable data transformation pipelines using dbt and PySpark, with a strong focus on data quality, performance optimization, and CI/CD practices. Proficient in collaborating with cross-functional teams to translate business requirements into operational data solutions.

Highest-signal resume keywords

Dbt Core DevelopmentAnalytics EngineeringPySpark Transformation ScriptsApache IcebergSQL Performance Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Transformation PipelinesData Quality ChecksPerformance OptimizationComplex SQL TransformationsJob OrchestrationData ModellingRegression TestingData ValidationSAS-based ETLVersion Control

Soft Skills

CollaborationCommunication

Tools & Technologies

DbtApache SparkDagsterGit

Industry Keywords

Data EngineeringCI/CD PracticesLegacy System MigrationBusiness AnalysisAutomated Deployment

Tech Stack

Tools & technologies

ApacheETLPySparkSparkSQL

About the role

Key responsibilities & impact

Design and develop scalable, reliable data transformation pipelines and workflows
Optimise the performance and execution times of dbt projects
Design, implement, and document data quality checks and control tests using dbt capabilities
Establish automated regression testing and validation procedures to ensure pipeline output quality and consistency
Promote and share best practices for maintaining, managing, and evolving dbt projects across the team
Analyse business requirements and translate business analysis documentation into robust, operational data transformation pipelines
Work as part of the Development team in close cooperation with a major client’s IT team on site

Requirements

What you’ll need

University degree in Computer Science, Information Technology, Systems Engineering, or relevant discipline, combined with minimum 12 years of relevant working experience in IT
Hands-on experience with dbt, preferably dbt Core, for designing, maintaining, testing, documenting, and extending production-grade analytics transformation projects
Experience in analytics engineering and modern data modelling, including layered architectures, reusable macros, data quality controls, and CI/CD practices
Experience developing PySpark transformation scripts for large-scale data processing; Spark job optimisation would be an asset
Hands-on experience with Apache Iceberg, including partition and schema evolution, snapshot management, and time travel
Experience with job orchestration and scheduling tools such as Dagster
Strong knowledge of SAS-based ETL and legacy codebases; experience migrating SAS workflows to dbt is a strong asset
Excellent SQL skills, including complex transformations, performance optimisation, and incremental processing
Good understanding of Apache Spark execution, partitioning strategies, file layout optimisation, and performance tuning
Strong knowledge of data validation, reconciliation, and testing for migrating legacy systems to dbt and PySpark
Knowledge of version control and collaborative development practices, including Git, code reviews, release management, and automated deployment pipelines
Excellent command of the English language

Benefits

Comp & perks

Competitive remuneration based on qualifications and experience
Option of contract basis or remuneration with full benefits package
Confidential application process
International, multilingual and multicultural work environment
Equal Employment Opportunity