Working Student Data Engineer – Python, SQL, Cloud Platforms

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🔥 0 minutes ago

🇩🇪 Germany – Remote

⏱ Part Time

⚪️ Entry-level

🔙 Backend Engineer

🚫👨‍🎓 No degree required

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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datavent.io

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2024

🤝 B2B

🤖 Artificial Intelligence

💼 Consulting

B2B • Artificial Intelligence • Consulting

datavent. io is a B2B data engineering and platform consulting firm that builds cloud-native, AI-ready data platforms and lakehouse architectures for analytics and production AI. They deliver end-to-end services — architecture, ingestion, transformation, modeling, MLOps/RAG pipelines, vector stores/feature stores, and ongoing platform stewardship — on customers' clouds and stacks (AWS, GCP, Azure, Snowflake, Databricks or on-prem) with a no-vendor-lock-in approach. The company emphasizes production outcomes (ship production pipelines, not prototypes), rapid delivery, and integrations across many data sources for enterprises in industries like banking, telecom, manufacturing and B2B SaaS.

📋 Description

• 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

• 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

• 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

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