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# Data Engineer

- **Company:** Celus.
- **Location:** München, Germany
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Business Analytics Applications, Databases, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Python (Programming Language), PostgreSQL, MongoDB, Snowplow, SQL Databases, Systems Integration, Pyspark, Information Technology, Data Pipelines, Databricks
- **Published:** August 1, 2026
- **Apply:** https://www.careerjet.de/jobad/decf09263f2bdb365ee156ef80caa3db2c

## About the Role

* Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related technical field.
 * Hands-on experience as a Data Engineer, with practical experience building ETL and data ingestion pipelines.
 * Strong experience with Databricks (our primary data platform), SQL, and Python, PySpark
 * Experience working with Snowplow for event tracking and analytics data collection. Experience with dbt for data transformation is highly advantageous.
 * Exposure to at least one of PostgreSQL, MongoDB, or DuckDB,
 * Excellent communication skills and the ability to collaborate and problem solve effectively
 * An interest in mentoring colleagues and contributing to a data-driven culture is highly valued.

## Description

At CELUS, we're building the platform where component adoption happens and are hiring a Data Engineer (F/M/D), who will play a key role in building reliable, scalable data pipelines and ingestion processes that create real impact across our product and the wider business, while supporting analytics initiatives across the business.
Your responsibilities will include:

 * Design, build, and maintain scalable ETL and data ingestion pipelines using Databricks, PySpark, supporting the full lifecycle from development through deployment and optimisation.
 * Configure and support Snowplow event tracking and data collection, ensuring high-quality behavioural data is available for analytics and reporting.
 * Develop and maintain data transformation and semantic models using SQL and dbt, delivering trusted datasets that enable self-service analytics and business insights.
 * Collaborate with software engineers and business stakeholders to understand data requirements, improve data quality, and support integrations across our data platform, including APIs and databases such as PostgreSQL, MongoDB, or DuckDB.
 * Contribute to the continuous improvement of our data platform by monitoring pipeline performance, sharing best practices, mentoring colleagues, and exploring new technologies that enhance our data engineering capabilities.


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