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
responsibilities :
designing and implementing Azure Data solutions for handling extensive and/or unstructured datasets;
utilizing Azure Databricks and other services for advanced data processing, analytics, and machine learning tasks, optimizing performance and scalability;
collaborating with solution architects to establish and promote data engineering best practices and standards within the Azure ecosystem;
implementation, optimization and testing of modern DWH/Big Data solutions based on Azure cloud platform and Continuous Delivery / Continuous Integration environment;
data processing efficiency improvement, migrations from on-prem to public cloud platforms;
mentoring and guiding junior data engineers in Azure-specific technologies, fostering a culture of continuous learning.
requirements-expected :
strong experience in Big Data or Cloud projects in the areas of processing and visualization of large and unstructured datasets (in different phases of Software Development Life Cycle);
practical knowledge of the Azure cloud in Storage, Compute (+Serverless), Networking and DevOps areas supported by commercial project work experience;
very good knowledge of Python and SQL;
practical Azure cloud knowledge (for example from the MS Learn courses) supported with certificates (for example DP-900, DP-200/201, AZ-204, AZ-400);
experience with several of the following technologies: Data Lake Gen2, Event Hub, Data Factory, DataBricks, Azure DWH, API Azure, Azure Function, Power BI;
very good command of English.
offered :
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.
benefits :
sharing the costs of sports activities
private medical care
life insurance
no dress code
parking space for employees
extra social benefits
redeployment package
employee referral program
charity initiatives
access to courses e.g. Excel, VBA, RPA, Customer Care
