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 :
at least 5 years of 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.
benefits :
private medical care
sharing the costs of foreign language classes
sharing the costs of professional training & courses
life insurance
flexible working time
integration events
corporate sports team
no dress code
parking space for employees
extra social benefits
sharing the costs of tickets to the movies, theater
