2 months ago
Poznań, PolandMid Level
Responsibilities
- Design and implement Azure-based data solutions for large-scale and unstructured datasets.
- Develop and optimize data pipelines using Azure Data Factory, Databricks, Snowflake, or Microsoft Fabric.
- Collaborate with solution architects to define and implement data engineering best practices.
- Ensure data quality, scalability, and security across Azure-based solutions.
Requirements
- Strong experience in data engineering and working with Azure.
- Strong Python skills for data processing and automation.
- Hands-on experience with Databricks, Snowflake, or Microsoft Fabric.
- Strong communication skills and very good English language skills.
- Preferred qualifications include strong SQL and database optimization experience; DevOps, CI/CD, Terraform, or Bicep knowledge; familiarity with Azure Data Lake, Event Hub, Data Factory, Synapse Analytics, and Azure Functions; Docker and Kubernetes exposure; cloud security knowledge; real-time processing with Kafka or Spark Streaming; PySpark experience; and DP-900, DP-203, AZ-204, or AZ-400 certifications.
Benefits
- Permanent employment contract from the first day.
- Hybrid and flexible working model.
- Home-office equipment package.
- Private medical care with Medicover, life insurance, Capgemini Helpline, and NAIS benefit platform.
- Access to more than 70 training tracks with certification opportunities and learning platforms including Pluralsight, Coursera, Udemy Business, TED Talks, and SAP Learning HUB.
- Access to more than 20 professional communities through the Community Hub.
Tech Stack
Categories
Data Engineering
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.