Azure Data Engineering Expert @ Capgemini Polska Sp. z o.o.

YOUR PROFILE strong experience in data engineering very good experience with data-oriented Python (Polars, Pandas, Pyspark) very good experience with Microsoft Azure, especially Synapse is a plus Solid understanding of cloud architecture ITIL Strong analytical skills and customer focus Can rapidly adapt and respond to changes in environment and priorities Advanced English is a must Excellent communication skills with high customer focus Desirable: Database knowledge, PowerBI knowledge, experience in Bl Projects & DataVault 2.0 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 delivers state-of-the-art Data solutions. Our expertise primarily lies in Cloud & Big Data engineering, where we develop robust systems capable of processing extensive and complex datasets, utilizing specialized Cloud Data services across platforms like AWS, Azure, and GCP. We oversee the entire Software Development Life Cycle (SDLC) of these solutions, which involves not only leveraging data processing tools such as ETL but also extensive programming in languages like Python, Scala, or Java, coupled with the adoption of DevOps tools and best practices. The processed data is then made accessible to downstream systems through APIs, outbound interfaces, or is visualized via comprehensive reports and dashboards. Additionally, within our AI Center of Excellence, we undertake Data Science and Machine Learning projects with a focus on cutting-edge areas such as Generative AI, Natural Language Processing (NLP), Anomaly Detection, and Computer Vision.  YOUR TASKS Project aims at integrating and harmonize data from strategic platforms into our global data platform. We look for a data engineer to create, maintain and improve pipelines from source to harmonized layer and from harmonized layer to consumption layer for Power BI reporting. Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets. Business domains covered are around commercial insurance pricing & underwriting. WHAT YOU'LL LOVE ABOUT WORKING HERE 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, Cloud, IoT, Agile, AI. GET TO KNOW US 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.   ,[Developing new functionality within the Python-based ETL pipeline, Ongoing maintenance and optimization of existing pipelines, Planning the capacity and sizing of service components, as well as proactively managing cloud components, Initiating the planning and setup of new service components, Coordinating the operations and maintenance of related software, complex server infrastructure, and databases (such as Synapse, PowerBI, and local development environments), Service-related documentation must be maintained in accordance with customer technology standards, Monitoring services and managing SLA performance will be an ongoing task, Processes and configurations related to the environments must be documented, maintained, and optimized, Collaboration with various stakeholders, including development, architecture, rollout, and operations teams, as well as customers, will be necessary for managing releases, upgrades, and changes] Requirements: Data engineering, Python, pandas, Microsoft Azure, Communication skills, Cloud, ITIL, PowerBI 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.