Department/project description:

Insights & Data practice delivers cutting-edge data centric solutions.

Most of our projects are Cloud & Big Data engineering. We develop solutions to process large, also unstructured, datasets, with dedicated Cloud Data services on AWS, Azure or GCP.

We are responsible for full SDLC of the solution: apart from using data processing tools (e.g., ETL), we code a lot in Python, Scala or Java and use DevOps tools and best practices. The data is either exposed to downstream systems via API, outbound interfaces or visualized on reports and dashboards.

Within our AI CoE we deliver Data Science and Machine Learning projects with focus on NLP, Anomaly Detection and Computer Vision.

Additionally, we are exploring the area of Quantum Computing, searching for practical growth opportunities for both us and our clients.

Currently, over 250 of our Data Architects, Engineers and Scientists work on exciting projects for over 30 clients from different sectors (Financial Services, Logistics, Automotive, Telco and others)

Come on Board! :)

Your daily tasks:

  • collecting requirements and proposing technical solutions in cooperation with the client;
  • implementation and optimization of data warehousing and ETL processes (disk-based and in-memory processing);
  • designing physical and logical data models based on the star/snowflake schema or OLAP Cubes;
  • test automation and code deployment using DevOps & CI/CD best practices.

Frequently used technologies:

  • ETL tools e.g. Informatica, SSIS, DataStage, ODI, Talend
  • SQL
  • Data Visualization tools e.g. Power BI, Tableau, QlikSense
  • Python
  • Cloud Data Services: Azure / AWS / GCP

Our expectation:

  • have at least 3 years of commercial experience in data warehouse (DWH) and Business Intelligence projects using ETL tools (e.g. Informatica PowerCenter, Talend, IBM InfoSphere DataStage, Ab Initio) and SQL language;
  • familiarity with at least one relational database system (e.g. Oracle, Teradata, MS SQL Server or PostgreSQL);
  • knowledge of one or more of the following (or similar) tools and technologies: IBM Cognos, SAP Business Objects, Microsoft Power BI, Tableau, QlikView, OBIEE;
  • practical knowledge of software engineering best practices;
  • knowledge of at least one of the programming languages: Python / Scala / Java / Bash;
  • good command of English or German.