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# Senior Data Engineer - Databricks (m/f/*)

- **Company:** Ultra
- **Location:** Berlin, Germany (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Continuous Integration, Data Systems, Data Warehousing, Distributed Computing Environment, Machine Learning, Performance Tuning, SQL Databases, Data Processing, Cloud Platform System, Azure Data Factory, Apache Spark, Git, Data Lakes, Pyspark, Kubernetes, Terraform, Software Version Control, Data Pipelines, Databricks
- **Published:** June 11, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=99712c88b1e7f214

## About the Role

Do you have experience in Terraform?, * Strong hands-on experience with Databricks and Apache Spark (PySpark, SQL, and/or Scala).

 * Experience building and operating cloud-based data platforms on AWS, Azure, or GCP.
 * Solid understanding of distributed data processing, data modeling, data warehousing, and performance optimization.
 * Experience with CI/CD practices and version control systems such as Git.
 * Familiarity with orchestration frameworks such as Airflow, Azure Data Factory, or Databricks Workflows.
 * Experience working in agile and cross-functional environments.
 * Strong communication skills in English & German.
 * A collaborative mindset and passion for building reliable, scalable, and maintainable data solutions.

## Description

In this role, you will work closely with data engineers, data scientists, architects, and business stakeholders to design and implement robust data solutions using modern cloud and data technologies., * Design, implement, and maintain scalable data pipelines on the Databricks Lakehouse Platform using technologies such as Apache Spark and Delta Lake.

 * Develop and optimize batch and streaming data workflows that support analytics, machine learning, and business intelligence use cases.
 * Collaborate with cross-functional teams to translate business and data requirements into reliable, production-ready solutions.
 * Improve the performance, scalability, and cost efficiency of data processing workloads within Databricks environments.
 * Support the implementation of best practices for data quality, governance, security, and compliance.
 * Contribute to architectural discussions and help shape modern data platform strategies for clients.
 * Mentor and support junior engineers while fostering knowledge sharing across the team.


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