
Azure Data Engineer @ Capgemini Polska Sp. z o.o.
2 days ago
- 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.
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 TEAMInsights & 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
- 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.
- Access to over 70 training tracks with certification opportunities (e.g., GenAI, Excel, Business Analysis, Project Management) on our NEXT platform. Dive into a world of knowledge with free access to Education First languages platform, Pluralsight, TED Talks, Coursera and Udemy Business materials and trainings.
- Enjoy hybrid working model that fits your life - after completing onboarding, connect work from a modern office with ergonomic work from home thanks to home office package (including laptop, monitor, and chair). Ask your recruiter about the details.
- Award-Winning Stability & Culture: Become part of an organization celebrated as "Top Employer Poland 2024" - in the audit our stable and supportive work environment scored 100%
Capgemini is committed to diversity and inclusion, ensuring fairness in all employment practices. We evaluate individuals based on qualifications and performance, not personal characteristics, striving to create a workplace where everyone can succeed and feel valued.
Do you want to get to know us better? Check our Instagram — @capgeminipl or visit our Facebook profile — Capgemini Polska. You can also find us on TikTok — @capgeminipl.
ABOUT CAPGEMINICapgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 360,000 team members globally in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.
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,[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: Data engineering, Azure, Python, Databricks, Snowflake, SQL, DevOps, CD pipelines, Infrastructure as Code, Terraform, Bicep, Data Lake, Docker, Kubernetes, Cloud, Security, Kafka, Spark Streaming, PySpark Additionally: Training budget, Sport subscription, Private healthcare, International projects, Free coffee, Bike parking, Free parking, Mobile phone, In-house trainings, Modern office, No dress code.-
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