Manager - Data Engineer IT Squad.Group Strategy and Transformation at MTN

Responsibilities

Pipeline Design & Optimisation

• Take full ownership of the design, development, and maintenance of real-time and batch data pipelines that power telco, geospatial, and behavioural analytics across the enterprise.
• Leverage tools such as Spark, Kafka, SQL, and Python to build high-performance pipelines that meet business SLAs for latency, throughput, and resilience.
• Drive continuous improvement in pipeline architecture to optimise cost, scalability, and cross-system efficiency in hybrid cloud environments.
• Act as the key integration point between IT systems and the DataCo analytics ecosystem, ensuring seamless data flow across platforms.

Big Data Infrastructure Management

• Lead the operation and optimisation of MTN’s large-scale data infrastructure, including Hadoop, Spark, Databricks, and other distributed computing frameworks.
• Manage ingestion and processing of high-volume telco data (e.g., CDRs, DPI, trace data, mobility signals), ensuring consistency, availability, and security.
• Partner with IT and infrastructure teams to pre-empt system constraints and deliver scalable solutions that meet OpCo and Group data needs.

Data Quality & Validation

• Proactively embed end-to-end data quality controls into ingestion workflows, including validation, anomaly detection, and cleansing pipelines.
• Champion standardisation of metadata, lineage tracking, and access control across pipelines in collaboration with governance and security teams.
• Ensure adherence to MTN Group’s data privacy, compliance, and Responsible AI policies, enabling trusted internal and external data use.

Analytics & AI Readiness Enablement

• Deliver ML- and analytics-ready feature datasets with strong version control and reproducibility across markets and use cases.
• Partner with Data Science, BI, and GIS teams to co-create structured data layers for predictive models, dashboards, and industry-specific insights.
• Establish reusable components (e.g., curated tables, transformation logic, catalogues) that accelerate time-to-value across OpCos.

DevOps & CI/CD Integration

• Implement automated deployment pipelines using CI/CD tooling (e.g., GitLab CI, Terraform, Azure DevOps), enabling agile and reliable delivery of data engineering assets.
• Lead monitoring and observability practices across pipelines, using performance dashboards, alerts, and health checks to ensure system uptime and recovery readiness.
• Work hand-in-hand with IT platform teams to streamline deployment in hybrid and federated environments, accelerating delivery cycles and reducing operational friction

Qualifications

Education:

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical discipline (required)
• Master’s degree in Data Engineering, Cloud Infrastructure, or Big Data Architecture (advantageous)
• Industry certifications in cloud platforms (Azure, GCP, AWS), big data frameworks (Spark, Hadoop), or DevOps/DataOps tools are strongly advantageous

Experience:

• Minimum of 5- 8 years of experience in data engineering, with at least 3+ years in a senior or lead capacity, managing high-throughput data environments
• Demonstrated experience designing and optimising real-time and batch pipelines across cloud and on-prem infrastructures
• Proven track record in telco-scale data processing, including handling of CDRs, DPI logs, mobility signals, or similar high-volume signals
• Experience driving cross-functional delivery in partnership with platform teams, IT infrastructure, governance, and product squads
• Familiarity with data monetisation, data productisation, or data enablement in platform or consulting contexts is preferred

Competencies:

• Data Pipeline Mastery: Expert in building and scaling real-time and batch data pipelines using Spark, Kafka, SQL, and Python
• Big Data Infrastructure Leadership: Deep knowledge of distributed systems (Hadoop, Databricks, Hive) and hybrid cloud environments
• Cloud & DevOps Integration: Skilled in CI/CD, containerisation (Docker, Kubernetes), IaC, and observability tools for data systems
• Governance & Compliance Alignment: Designs pipelines that embed data lineage, security tagging, access control, and policy enforcement
• System Optimisation: Drives performance tuning, cost efficiency, fault tolerance, and workload automation at scale
• Team Enablement: Mentors data engineers, drives capability uplift across OpCos, and standardises reusable engineering components
• Cross-functional Influence: Proactively engages with IT, security, architecture, and analytics functions to accelerate delivery and integration

Apply Before 10/13/2025