Amsterdam
3 weeks ago
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Data Engineer

Budget Thuis

Data Engineer

Budget Thuis is seeking a Data Engineer to help build its data platform from scratch, including evaluating and choosing the data stack, building and maintaining data pipelines, and embedding data quality checks. The role requires hands-on experience with modern cloud data stacks, dbt, and orchestration tools, and offers a hybrid work model with a competitive salary.

HybridFull-timeEntry LevelDbtApache Airflow

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

Hybrid working (50/50); 1 month per year fully remote

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)
dbtApache AirflowDagsterCloud Data WarehouseData Quality ChecksSQLData PipelinesETLTestingCollaborationCommunicationProblem Solving
Soft Skills
CollaborationCommunicationCuriosityGrowth MindsetFeedbackProblem Solving

Preferred Qualifications

Technical (Nice-to-have)
AzureAzure Data LakeDatabricksAzure Event HubsData GovernanceData LineageData CatalogingQuality MonitoringBI

Key Responsibilities

  • Help evaluate and choose the tools for our data stack: data warehouse, ELT, and orchestration.
  • Build and maintain data pipelines of low to medium complexity once the foundation is in place.
  • Add data quality checks to every pipeline change: null checks, row counts, schema validation, and dbt tests (or equivalent) as standard practice, not an extra step.
  • Break your work into small, deployable increments and keep pull requests focused.
  • Monitor pipeline outputs after every deployment and keep the codebase easy to work with.
  • Respond quickly to pipeline failures, investigate the root cause, and escalate when an issue is bigger than you.
  • Review pull requests with constructive feedback, pair with teammates on complex work, and support colleagues where needed.
  • Communicate early when changes affect downstream consumers such as BI, ML, or customers, and prioritize based on customer impact.
  • Build a concrete growth plan with your manager and share what you learn from mistakes.
Data EngineerData PlatformCloud Data StackdbtAirflowDagsterHybridEnergyUtilitiesAmsterdam