Working Student Data Engineer – Python, SQL & Cloud Platforms

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About AgentixLake

AgentixLake GmbH is a Data and AI engineering consultancy based in Hamburg, Germany. We design, build and operate production-grade data platforms and AI systems in our customers’ cloud accounts or on-premises environments. We are an AWS Services Partner and a Certified Services Partner in Anthropic’s Claude Partner Network. Our commercial focus is DACH and the Gulf region, alongside selected international opportunities.

Your role

Build the pipelines and data models that people can depend on. You will own defined components of our data engineering projects, from understanding a source system to delivering tested transformations and monitoring how they run.

Our data platform engineering work connects operational systems with analytics and AI applications. Depending on the project, you will work with cloud warehouses, lakehouse architectures and the data quality and reliability practices that support production use.

What you will do

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

Develop data models and dbt transformations with clear definitions, tests and documentation.

Implement incremental processing, schema checks and reconciliation so changes and data issues are visible.

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 and explain their impact on downstream users.

What you bring

Current university enrolment in computer science, data science, business informatics or a related technical discipline.

Strong SQL and practical Python, supported by pipelines or data models you have built and maintained for actual users or team workflows.

A sound understanding of data modelling, incremental loads, data quality and the operational behaviour of scheduled pipelines.

Experience with version control and testing, plus practical exposure to a cloud platform, warehouse or orchestration tool.

The 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. You do not need experience with every technology; show us where you have developed depth.

What you can expect

You will work on data systems with clear users and delivery requirements, collaborate directly with experienced engineers and the founders, and receive substantive code review. Your part-time responsibilities and schedule will be planned around your studies.

How to apply

Use the Apply button on this page to submit your CV, current study details, location and weekly availability. Describe one pipeline or data model you delivered, the decisions you owned and how you tested or improved its reliability. An anonymised example is welcome; please do not share confidential client material.

We welcome applicants of all backgrounds. If the core responsibilities match your experience, we would like to hear from you.

Stay connected

Follow AgentixLake on LinkedIn for practical engineering insights, project updates and future opportunities. Following is optional and does not influence recruitment decisions.

LinkedIn: https://www.linkedin.com/company/agentixlakegmbh/

Website: https://agentixlake.com/

Explore our AWS data and AI platform work: https://agentixlake.com/platform-aws