Azure Data Engineer

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.

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.

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.

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.

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