Working Student Data Engineer – Python, SQL, Cloud Platforms

datavent.io

. Build Python and SQL pipelines to ingest and transform data from APIs, databases, files or event sources .

Posted 10/31/2026part-timeRemote • GermanyEntry LevelWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining data pipelines using Python and SQL, with a strong focus on data modeling, incremental processing, and cloud platform integration. Capable of managing data engineering projects from analysis to deployment while ensuring data quality and operational efficiency.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyData Pipeline DevelopmentCloud Platform ExperienceDbt Transformations

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingIncremental LoadsData Quality AssuranceVersion ControlTesting Methodologies

Soft Skills

Clear CommunicationProblem-SolvingOwnership of Deliverables

Tools & Technologies

AirflowDagsterAWSSnowflakeDatabricksBigQueryApache IcebergTerraform

Industry Keywords

Data EngineeringCloud Data PlatformOrchestration ToolsData TransformationAPI Integration

Tech Stack

Tools & technologies

AirflowApacheAWSBigQueryCloudPythonSnowflakeSQLTerraform

About the role

Key responsibilities & impact

Build Python and SQL pipelines to ingest and transform data from APIs, databases, files or event sources
Develop data models and dbt transformations with definitions, tests and documentation
Implement incremental processing, schema checks and reconciliation
Configure orchestration and monitoring
Investigate failed runs and improve recovery and troubleshooting
Contribute to cloud data platform components, infrastructure configuration and deployment workflows
Use Git, pull requests and code review to deliver maintainable changes
Explain the impact of changes on downstream users
Own defined components of data engineering projects from source-system analysis through tested transformations and monitoring

Requirements

What you’ll need

Current university enrolment in computer science, data science, business informatics or a related technical discipline
Strong SQL and practical Python
Experience building and maintaining pipelines or data models for actual users or team workflows
Sound understanding of data modelling, incremental loads, data quality and operational behaviour of scheduled pipelines
Experience with version control and testing
Practical exposure to a cloud platform, warehouse or orchestration tool
Ability to own a well-scoped deliverable, investigate problems systematically and communicate clearly in English
Experience with dbt, Airflow, Dagster, AWS, Snowflake, Databricks, BigQuery, Apache Iceberg or Terraform is valuable

Benefits

Comp & perks

Working student part-time schedule planned around studies
20 days of annual leave
20 hours/week
Substantive code review
Direct collaboration with experienced engineers and founders
3-month probation period