Data Engineer

vor 24 Stunden

Stuttgart, Baden-Württemberg, Deutschland Annapurna Vollzeit

Freelance Data Engineer

Location: Fully Remote within EU + UK

Contract Type: Freelance 6+ Months

About the Company

A leading European organisation in the mobility and smart infrastructure sector is seeking a skilled Data Engineer to support the ongoing development of its modern, cloud-based data platform. The company operates large-scale digital systems powering connected parking, transport, and urban mobility solutions across multiple countries. This role will play a key part in transforming operational and customer data into actionable insights to drive efficiency and innovation.

Key Responsibilities

  • Design, build, and maintain data pipelines and ETL/ELT workflows within the Azure Databricks environment.
  • Develop and scale data platform components using Terraform and Infrastructure as Code (IaC) best practices.
  • Manage and optimise data storage, cataloging, and governance through Azure Unity Catalog.
  • Automate and orchestrate complex data workflows using Databricks Workflows and Delta Live Tables (DLT) for reliable, end-to-end pipeline management.
  • Own and maintain CI/CD and DevOps processes to ensure smooth deployment and infrastructure automation.
  • Establish and uphold data modeling standards that support scalability, consistency, and data accessibility across systems.
  • Ensure data quality, reliability, and performance across all stages of the data lifecycle.
  • Work independently on multiple initiatives, delivering robust and scalable data engineering solutions.
  • Contribute to the ongoing improvement of the data platform architecture and internal engineering best practices.

Required Skills & Experience

  • 5-8 years of experience in data engineering or a related role.
  • Hands-on expertise with the Azure ecosystem - particularly Azure Databricks, Azure Data Lake, and Azure Unity Catalog.
  • Proven experience using Terraform and implementing Infrastructure as Code (IaC).
  • Strong understanding of data platform engineering, pipeline design, and ETL/ELT processes.
  • Solid grounding in data modeling (conceptual, logical, and physical) and building scalable data structures.
  • Proficiency in PySpark, with strong understanding of Spark architecture, and working knowledge of Scala and SQL for advanced data transformations.
  • Experience managing CI/CD pipelines and DevOps automation for data infrastructure.
  • Excellent analytical, problem-solving, and communication skills.
  • Comfortable working independently in a fast-paced, agile environment.

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