As a Senior Manager – Data Engineer, you will play a pivotal role in shaping MTN’s data-driven future by providing strategic direction, technical expertise, and leadership to a team of talented data engineers. You will guide the team in architecting, developing, and optimizing complex data systems while driving best practices and fostering a culture of collaboration, creativity, and continuous improvement.
Key Responsibilities
Leadership & Team Management
- Provide strategic and operational leadership to the data engineering team.
- Foster a collaborative and innovative work culture, ensuring team alignment with organizational goals.
- Mentor and develop mid- and junior-level engineers, promoting professional growth and technical excellence.
Data Engineering Strategy
- Develop and implement robust data management strategies to support organizational goals.
- Lead the design and implementation of scalable data architectures, models, and solutions.
- Ensure data systems’ availability, reliability, and performance by maintaining advanced infrastructures such as databases, data lakes, and data warehouses.
Technical Excellence
- Oversee the adoption of Agile methodologies and foster effective Agile practices within the team.
- Review technical designs, troubleshoot complex data issues, and ensure adherence to best practices.
- Collaborate with cross-functional teams, including product management and marketing, to create innovative solutions through workshops and co-creation.
Collaboration & Stakeholder Engagement
- Partner with data scientists, analysts, and other departments to understand and meet their data needs.
- Facilitate clear and regular communication with stakeholders, providing progress updates and resolving impediments.
Performance Monitoring
- Define and track key performance indicators (KPIs) to measure team and project success.
- Regularly evaluate the performance of initiatives, providing insights and recommendations for improvement.
Innovation & Research
- Lead research initiatives and competitive analyses to inform strategic decisions.
- Create and promote a knowledge ecosystem for sharing data engineering best practices.
Qualifications
Education:
- Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field.
- Relevant certifications in data engineering or cloud platforms (preferred).
Experience:
- 8+ years of relevant work experience, including 5–8 years in data engineering or a related role.
- Expertise in designing and implementing scalable data solutions.
- Proven experience in architecting and optimizing data infrastructure in fast-paced, technology-focused environments.
Skills:
- Proficiency in programming languages such as Python, Java, or Scala.
- Expertise in data modeling, ETL processes, and data integration techniques.
- Strong knowledge of data processing frameworks and tools (e.g., Apache Spark, Hadoop, Kafka).
- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
- Proficient in design software (e.g., Figma).