Requirements

Expected technologies

SQL

Python

Operating system

Windows

Our requirements

• Several years of experience with cloud services, ideally Microsoft Azure: Azure Data Factory, Azure Data Lake, Databricks/Spark, Function Apps, CI/CD, Terraform, Unity catalog.
• Hands-on expertise with Azure Services and Databricks Data Intelligence Platform.
• Strong skills in data curation, semantic modeling, and large-scale transformations using Python, PySpark, and SQL.
• Knowledge of MLOps principles and hands-on experience with MLflow.
• Experience building and managing analytical solutions, including deployment, monitoring, and scaling solutions.
• Experience in implementing Infrastructure as Code and CI/CD automation for data platforms using Terraform.
• Agile working experience, with excellent collaboration, problem-solving, and communication skills.
• Ability to work with Agile methodologies (SAFe/Scrum) and manage iterative design improvements.

Your responsibilities

• As a Data Engineer, you will play a pivotal role in defining and executing analytics and BI requirements. You will design, develop, and support our cloud-based solutions, ensuring seamless data integration and transformation, and furthermore:
• Collaborate with internal customers to define analytics and BI requirements.
• Build ETL pipelines using Azure PaaS tools, SQL, and/or Python on a Spark-based analytics platform.
• Design, develop, and support cloud-based analytics solutions and applications.
• Provide technical feedback to solution architects and developers.
• Perform data exploration and modeling to enhance data-driven decision-making.