Azure Data Engineer @

2 tygodni temu


Wrocław, Województwo dolnośląskie, Polska Capgemini Polska Sp. z o.o. Pełny etat

Your Profile: At least 3 years of experience in data engineering, including 1+ year working with Azure. Strong skills in Python for data processing and automation. Hands-on experience with one of the following: Databricks, Snowflake, or Microsoft Fabric. Very good communication skills and strong 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. About Insights & Data: 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. Your Profile: At least 3 years of experience in data engineering, including 1+ year working with Azure. Strong skills in Python for data processing and automation. Hands-on experience with one of the following: Databricks, Snowflake, or Microsoft Fabric. Very good communication skills and strong 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. ,[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.] Requirements: Azure, Data engineering, Python, SQL, DevOps, Azure Data Factory, Azure Synapse Analytics, Docker, Kubernetes, CI/CD Additionally: Training budget, Private healthcare, International projects, Free parking, In-house trainings.



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