Data Engineer
Role details
Job location
Tech stack
Job description
We are looking for an experienced and solution-oriented Azure Data Platform Engineer to develop, operate, and optimize our modern Azure-based data platform. In this role, you will focus on Azure, Databricks, data infrastructure, and CI/CD, supporting multi-tenant environments and enabling reliable, scalable data solutions., * Develop a Modern Azure Data Platform: Design, build, and operate end-to-end data solutions using Azure Data Factory, Azure Data Lake Storage Gen2, Databricks, and Azure Synapse Analytics.
- Create Data Pipelines: Develop and maintain scalable ETL/ELT pipelines using PySpark and Spark, with a strong focus on data quality, reliability, and performance.
- Multi-Tenant & Environment Support: Support and operate multi-tenant data platforms across multiple environments (development, test, production) with clear separation and governance.
- Infrastructure & Platform Operations: Provision, configure, and maintain Azure data infrastructure, ensuring stability, security, and scalability.
- CI/CD for Data Platforms: Build and maintain CI/CD pipelines for data pipelines and Databricks workloads, enabling automated deployments across environments.
- Cost-Efficient & Best-Practice Azure Usage: Apply Azure best practices to optimize performance and cost, including resource sizing, lifecycle management, and cost monitoring.
- Collaboration with BI & Data Teams: Work closely with BI and data teams to support efficient data models and reporting solutions.
- Data Governance & Security Basics: Support data governance requirements such as access control, secure data handling, and basic metadata management.
Requirements
Do you have experience in Spark?, * Azure Data Platform Experience: Several years of hands-on experience with Azure Data Factory, ADLS Gen2, Databricks, and Azure Synapse Analytics.
- PySpark & Spark: Strong experience building distributed data processing pipelines using PySpark and Spark.
- ETL / ELT Knowledge: Solid understanding of ETL/ELT concepts and data modeling practices.
- CI/CD & Automation: Experience with CI/CD pipelines for data workloads and basic automation of deployments.
- SQL Skills: Strong SQL skills and experience optimizing analytical queries.
- Data Formats: Practical experience with Parquet and/or Avro.
- Infrastructure Awareness: Good understanding of Azure resource structure, environments, and operational best practices.
- Analytical & Team-Oriented Mindset: Solution-focused approach with the ability to work independently and collaboratively.
- Language Skills: Fluency in English is required; knowledge of German is an advantage.