The Data Engineer holds the primary responsibility for readying and manipulating data for further analysis, encompassing ETL processes, and providing support for testing throughout the development stages. They extract, transform, and integrate data from various sources to construct datasets conducive to reporting, analysis, and analytics. The overarching aim is to optimize efficiency by aligning data systems with the objectives of the business. The role involves collaborating with a Business Analyst and a Data Architect/Modeller for testing endeavors.
Responsibilities:
- Preparing, transforming, and model data while addressing conflicting data sources and irregularities.
- Aid in delivering Business Intelligence (BI) and analytical solutions to users through active participation in Agile development activities.
- Implementing strategies to enhance data reliability and quality.
- Merging raw data from disparate sources into coherent, machine-readable formats.
- Designing and testing architectures facilitating data extraction and transformation for predictive or prescriptive modeling.
- Managing technical testing services across the entire delivery process, encompassing system integration, performance engineering, and unit testing.
- Collaborating with the Business Analyst, Data Architect, and Data Visualization Developer during these testing phases.
- Collaborating with the Group IT team to ensure compliance with architectural guidelines and contribute insights for their enhancement.
Minimum Requirements:
- Bachelor’s degree in computer science, IT, or a related field; a Master’s degree is advantageous.
- Extensive expertise in designing, developing, and testing ETL processes.
- Proficiency in batch and real-time data processing.
- Proven experience in extracting valuable insights and features from extensive datasets using relevant toolsets.
- Familiarity with modern code development practices.
- Extensive hands-on experience with SAP ERP and BW/4HANA (both Frontend and Backend).
- Competence in relational and NoSQL data modeling methodologies.
- Proficiency in at least one packaged ETL tool.
- Technical prowess in data models, data mining, and segmentation techniques.
- Proficiency in BW Data modeling and SQL database design through practical experience.
- Data engineering certification (e.g., MS Azure Data Engineer or SAP Data Architects) is beneficial.
Desired Skills:
- SAP ERP and BW/4HANA
- (Frontend and Backend) relational
- NoSQL data modelling approaches