communicate data insights effectively. 4. Data Cleaning: Cleaning and preprocessing data to ensure accuracy
ensuring accuracy and completeness. Data Cleaning: Pre-process and clean data to prepare it for analysis, which
Power BI, Excel, BigQuery and other tools for data cleaning, report generation and analysis Finding data quality to solve data-related problems Skilled at data cleaning, aggregation, and the automation of repetitive data processing principles, data warehousing, cleaning, ETL and building scalable models and data pipelines
fundamentals The commitment to building software using clean code and industry best practices Proficiency in
fundamentals The commitment to building software using clean code and industry best practices Proficiency and
visually appealing and intuitive to use. Write clean, efficient, and maintainable code, following best
optimization. Perform bug fixes. Code Quality - Produce clean, efficient code based on expected standards. Ensure formulations. Develop extracts from scratch. System cleaning and stopping extracts that slow the software. customer brands and locations. Data Ingestion – Clean data that is sent to suppliers' global portals for
ensure the technical feasibility of designs. • Write clean, maintainable, and efficient code, following best control systems such as Git. • Ability to write clean, well-documented, and maintainable code. • Excellent
from over 200 source systems. The role involves cleaning and aggregating data through our pipeline. The
NET framework, Advanced C# features, API, GitHub, Clean architecture in .Net Core, Object Relational mapping(ORM)