Data Engineer(Azure)
Azure Data Engineer at Capgemini's Insights & Data team in Poznań, Poland (hybrid), designing and implementing Azure-based data solutions and pipelines for large-scale datasets. Core stack: Azure (Data Factory, Synapse), Databricks/Snowflake/Microsoft Fabric, and Python, with DevOps and streaming tech as a plus.
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Strong experience in data engineering, including working with Azure
- Strong Python for data processing and automation
- Hands-on experience with Databricks, Snowflake, or Microsoft Fabric
- Strong communication skills and very good English
Nice to have
- Strong SQL skills and database optimization experience
- Knowledge of DevOps practices, CI/CD pipelines, and IaC tools (Terraform, Bicep)
- Familiarity with Azure services: Data Lake, Event Hub, Data Factory, Synapse Analytics, Azure Functions
- Exposure to containerization (Docker, Kubernetes) and cloud security best practices
- Experience with real-time data processing/streaming (Kafka, Spark Streaming)
- Hands-on experience with PySpark
- Certifications such as DP-900, DP-203, AZ-204, or AZ-400
Full description
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Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Your Team
Insights & Data is a dynamic team of over 400 professionals delivering cutting-edge data solutions. We specialize in Cloud & Big Data engineering, building scalable systems for complex datasets across AWS, Azure, and GCP. Our expertise spans the full Software Development Life Cycle (SDLC), utilizing modern data processing tools, advanced programming techniques, and DevOps best practices to create impactful solutions.**
Come on Board!**
Your Task
- 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.
Your Profile
- 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.
Nice to have:
- 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 You'll Love About Working Here
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Well-being culture: medical care with Medicover, private life insurance, and Multisport card. But we went one step further by creating our own Capgemini Helpline offering therapeutical support if needed and the educational podcast "Let's talk about wellbeing" which you can listen to on Spotify.