Azure Data Engineer

Technologies we use

About the project

Your responsibilities

• Design and implement Azure-based data solutions for large-scale and unstructured datasets.
• Develop and optimize data pipelines using Azure Data Factory, Databricks, or Snowflake.
• Collaborate with solution architects to define and implement best practices in data engineering.
• Ensure data quality, scalability, and security across all Azure-based solutions.

Our requirements

• Strong experience in data engineering, including working with Azure
• Strong Python for data processing and automation.
• Hands-on experience with one of the following: Databricks, Snowflake, or Microsoft Fabric.
• Strong communication skills and very good English language skills.

Optional

• Strong SQL skills and experience with database optimization.
• Knowledge of DevOps practices, CI/CD pipelines, and Infrastructure as Code (IaC) tools (Terraform, Bicep).
• Familiarity with key Azure services: Data Lake, Event Hub, Data Factory, Synapse Analytics, Azure Functions.
• Exposure to containerization (Docker, Kubernetes) and cloud security best practices.
• Experience in real-time data processing and streaming technologies like Kafka or Spark Streaming.
• Hands-on experience with PySpark.
• Certifications such as DP-900, DP-203, AZ-204, or AZ-400.

What we offer

• Practical benefits: permanent employment contract from the first day; hybrid, flexible working model; equipment package for home office; private medical care with Medicover; life insurance; Capgemini Helpline; NAIS benefit platform;
• Access to 70+ training tracks with certification opportunities; platform with free access to Pluralsight, TED Talks, Coursera, Udemy Business and SAP Learning HUB
• Community Hub that will allow you to choose from over 20 professional communities that gather people interested in, among others: Salesforce, Java, Could, IoT, Agile, AI.

Benefits