Engineer: Data & Exploration - MTN Ghana

Job Summary

The Engineer, Data and Exploration is responsible for exploring and analysing large datasets to extract meaningful insights that drive business decisions and innovations. The role involves designing and implementing data pipelines, as well as conducting exploratory data analysis and building prototypes to test hypothesis.

The role holder is expected to work closely and collaboratively with the data scientist to translate insights into actionable recommendations and solutions. Ensuring the optimization of data processes, data quality as well as implementing best practices for data exploration and analysis.

Job Context

• Evolution and highly competitive Fintech Industry
• Multi-regulated environment
• Environmental, social and governance prioritized
• Evolving Telco with a focus on business platform and digital
• Partnerships at the core of industry plans
• Regionalized structure
• Financial inclusion at the core of the government agenda
• Localisation is a key objective for business and government
• Brand Reputation
• Performance-driven environment
• Diverse cultural environment

Job Role

• Lead with data by defining, building, and owning end-to-end analytical solutions.
• Design and develop data pipelines to collect, process and store large volumes of data from various sources.
• Perform data exploratory analysis to uncover patterns, trends and flag anomalies within the data for correction.
• Build data models and prototypes to test hypothesis to support effective business decision making.
• Develop and implement algorithms and techniques to clean data and transform it for effective use and analysis for insights and reporting.
• Ingest and harmonize data from multiple sources (internal systems, APIs, external feeds) into unified, analytics-ready formats.
• Collaborate with data scientist and other analysts within the BI & Decision Support function to structure datasets that power dashboards, models, and advanced analytics.
• Go beyond pipeline building by embedding business logic, KPIs, and contextual tagging that make data immediately actionable for decision-making.
• Ensure data accuracy, consistency, and accessibility by implementing validation, monitoring, and governance frameworks.
• Work closely with BI, product, and business teams to translate data into actionable insights, ensuring engineering efforts are aligned with strategic goals.
• Develop and maintain adequate documentation for data exploration processes and algorithms.
• Development of ad-hoc reports as necessary.
• Stay updated on industry best practices and emerging technologies in data engineering and exploration.
• Communicate insights and findings to stakeholders, both internal and external through reports, dashboards and other effective visualization tools.
• Where required, escalate unsolvable issues to Data Scientist in a timeous manner.
• Other tasks and duties, as assigned.

Requirements

Education

• Degree in Data Engineering, Computer Engineering, Data Analytics, Data Science, Mathematics, Statistics, Computer Science, Information Technology, or related field.
• A post-graduate degree in a similar or related field is an advantage.

Experience

• A minimum of 3 years experience in Data Science / Engineering / Visualization is required.
• Experience in Fintech, banking or Telecom is preferred.
• Experience working in a global/multinational enterprise with a good understanding emerging markets is preferred.
• Experience in data analysis and management, business performance management and BI within the Fintech industry.
• Knowledge of modern Big Data platforms and Open-Source solutions to database, data analysis, and data management.
• Deep knowledge and experience in data reporting/visualization tools (Power BI, Tableau, etc.).
• Deep knowledge and experience in data analytics tools (SQL, Python, SAS, etc.).
• Experience working across global locations/ regions and have a grasp of political, social, infrastructure and integrity challenges.
• Experience working with cloud platforms such as AWS, Azure or Google Cloud is a plus.
• Strong communication and collaboration skills, with the ability to work effectively in a cross-functional team.
• Excellent problem-solving and analytical skills with the ability to think critically and creatively about data.

Competencies

Professional/Technical Competencies:

• Big data and analytics
• Data mining & modelling
• Data interpretation
• Data visualization & Reporting
• Statistical Analysis
• Quantitative Analytics
• Forecasting/predictive Analytics,
• Multivariate testing & optimization algorithm
• Business intelligence systems and tools
• Data science toolkits (SAS, R, SPSS)

Must live the MTN Values of

• Lead with Care, Collaborate with Agility, Serve with Respect, Can Do with Integrity, Act with Inclusion

Must exhibit the MTN Vital Behaviors of

• Complete Candor, Complete Accountability, Active Collaboration & Get it done.

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