Evaluator - Data scientist, Enterprise Business at MTN Nigeria in Victoria Island, Lagos

Purpose

Build premium quality data pipelines pushing reasoned initiatives. These initiatives will produce findings from our linked data, empowering the progression of the analytics-based strategic judgment capabilities of our enterprise. Link and model sophisticated distributed data sets to build repositories, which includes data warehouses, data lakes, using suitable technical solutions.  Oversee data associated situations ranging across dealing with small to large data sets, organized/unstructured or streaming data, extraction, transformation, curation, modelling, building data pipelines, recognizing right resources, drafting SQL/Java/Scala code, etc.

Explanation

• Design, formulate, enhance, and preserve data architecture and pipelines that follow ETL principles and business targets
• Assemble large, sophisticated data sets that meet operational / non-operational organizational needs
• Recognize, design, and execute internal process enhancements: automating documented guide methods, optimizing data dispatch, re-designing structure for greater scalability, etc.
• Build the structure necessary for most effective extraction transformation, and loading of data from a broad selection of data suppliers using SQL and AWS ‘big data’ technical solutions
• Build data analysis resources that utilize the data pipeline to offer practical findings into customer conversion, process effectiveness and other key business key indicators
• Keep data secure
• Head the assessment, execution and deploying of emerging resources and process for reasoned data engineering in order to enhance our productivity as a team
• Collaborate with data and data analysis professionals to strive for greater capability data operational structures
• Formulate and supply information exchange and education strategies on reasoned data engineering capabilities, guidelines, and methods
• Collaborate with business analysts and initiatives architects to formulate technical architectures for strategic enterprise projects and programs.

Qualifications Education:

First Academic qualification in Mathematics, Statistics, MIS, Computer Science, Engineering or other associated disciplines. Fluent in English