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Database Analytics Engineer
EUROPEAN DYNAMICS. Design and develop scalable, reliable data transformation pipelines and workflows .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and developing scalable data transformation pipelines using dbt, with a strong focus on data quality checks, performance optimization, and CI/CD practices. Proficient in analytics engineering, including PySpark and Apache Iceberg, while collaborating effectively with cross-functional teams.
Highest-signal resume keywords
Dbt Core DevelopmentAnalytics EngineeringPySpark Transformation ScriptsApache IcebergSQL Performance Optimization
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Transformation PipelinesData Quality ChecksPerformance OptimizationComplex SQL TransformationsData ValidationReconciliationCI/CD PracticesJob OrchestrationData ModellingVersion Control
Soft Skills
CollaborationCommunication
Tools & Technologies
DbtApache SparkDagsterGitSAS
Industry Keywords
Data EngineeringData ProcessingLegacy CodebasesAutomated DeploymentBusiness Analysis
Tech Stack
Tools & technologiesApacheETLPySparkSparkSQL
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
- Promote and share best practices for maintaining, managing, and evolving dbt projects across the team
- Analyse business requirements and translate business analysis documentation into operational data transformation pipelines
- Work within the Development team and cooperate closely with a major client’s on-site IT team
- Work at company premises or customer premises
Requirements
What you’ll need- University degree in Computer Science, Information Technology, Systems Engineering, or relevant discipline
- Minimum 12 years of relevant working experience in IT
- Hands-on experience with dbt, preferably dbt Core, for 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
- 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
- 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
- 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 handling
- Equal Employment Opportunity
- International, multilingual, and multicultural work environment
- Career opportunities within a dynamic company