Lead, Data Engineer

JOB DESCRIPTION
        
GENERAL JOB INFORMATION
Job Title:                                      Lead, Data Engineer
Organization/ Department:    Group Technology
Reports to:                                  Head, Data & Analytics / Business Information Management
Salary Grade/ Band:                4C
Direct Reports:                         Data Engineers
 

JOB PURPOSE
Reporting to the Head, Data & Analytics / Head, Business Information Management, the Team Lead, Data Engineering is responsible for leading the design, delivery, and operational excellence of Ecobank’s enterprise data platforms.

This role provides leadership across data engineering, data platform architecture, and data solution design capabilities, ensuring the availability of trusted, scalable, and secure data to support analytics, regulatory reporting, and advanced use cases across the Group.
The resource is accountable for the reliability, integrity, and continuous optimization of data environments, while working closely with business and affiliate teams to translate evolving requirements into robust, scalable data solutions.

JOB CONTEXT 
This position requires strong interpersonal and collaboration skills across business units, affiliates, and senior stakeholders, alongside the ability to translate complex business demands into scalable data solutions. It also demands clear ownership of continuous improvement initiatives, platform monitoring, and operational controls, while actively contributing to the evolution of data strategy, architectural direction, and governance frameworks.

KEY RESPONSIBILITIES
Strategically 
•    Define and drive the data engineering and platform roadmap, aligned with Group data strategy and evolving business priorities
•    Identify and lead opportunities to leverage data for business growth, operational efficiency, and regulatory compliance 
•    Architect and oversee the evolution of enterprise-scale data platforms and solutions, including Lakehouse and warehouse architectures
•    Provide strong solution design leadership, ensuring scalable integration across APIs, enterprise systems, and hybrid/multi-cloud environments
•    Establish and enforce data engineering standards, frameworks, and best practices across ingestion, modelling, processing, and delivery
•    Drive adoption of advanced analytics, AI/ML capabilities, and real-time data solutions to support enterprise use cases
•    Lead the development of data products and enterprise data assets that enable business insights and decision-making
•    Partner with business leaders, affiliates, and technology stakeholders to translate strategic requirements into scalable data solutions 
•    Shape and enforce data governance, privacy, and security frameworks, ensuring alignment with regulatory and risk requirements 
•    Build and develop a high-performing, future-ready data engineering team, driving capability uplift and knowledge sharing 
•    Define the future-state data architecture vision and continuously evolve platform capabilities based on emerging technologies and industry trends

Tactically and Operationally 
•    Lead the design, build, and deployment of scalable data pipelines (batch and real-time) supporting BI, analytics, and ML workloads 
•    Build and lead the delivery of data solutions and complex ETL workflows using Databricks, Spark, SQL, Python, and cloud-based data platforms.
•    Ensure the creation and maintenance of high-quality data models, semantic layers, and business-ready datasets 
•    Translate business requirements into practical, implementable data solutions, aligned with agile delivery practices 
•    Manage day-to-day data platform operations, ensuring availability, stability, and performance of data environments
•    Monitor, troubleshoot, and optimize data pipelines and platform components to ensure reliability and efficiency
•    Enforce and track SLA compliance for data delivery, reporting timelines, and pipeline execution 
•    Implement and maintain data quality controls, validation processes, and integrity checks across all data assets
•    Define and implement CI/CD pipelines, version control, and release management practices for data engineering workflows 
•    Collaborate with Data Science teams to enable data pipelines for model development, training, and deployment 
•    Ensure proper data classification, documentation, and metadata management within the platform 
•    Oversee backup, recovery, and disaster resilience processes to safeguard critical data assets 
•    Lead and coordinate execution across distributed engineering teams and affiliate environments 
•    Remain current on industry trends and best practices, and inform the future direction of our data vision, architecture, and strategy

JOB PROFILE
Experience & Qualifications 
•    Minimum 7 years’ progressive experience in data engineering, data platform development, or a related discipline, with a strong track record of delivering measurable business outcomes, including at least 3+ years in a team leadership role
•    Demonstrable experience in designing, building, and managing enterprise-scale data platforms and data solutions, preferably within financial services or other highly regulated environments
•    Sound understanding of banking operations, financial data structures, and regulatory reporting requirements (is an advantage)
•    Strong hands-on expertise in modern data engineering technologies, including Databricks, Spark, SQL, Python, and Azure-based data services such as Data Factory, Synapse, and Data Lake architectures
•    Deep technical knowledge of data pipeline design (ETL/ELT), streaming architectures, API integrations, and data modelling across data warehouse and Lakehouse environments, supported by solid understanding of relational and NoSQL database design principles
•    Experience working within big data ecosystems and distributed data processing environments, with a focus on scalability and performance
•    Good working knowledge of data governance, metadata management, data lineage, and data security practices, including regulatory compliance considerations
•    Strong communication, stakeholder engagement, and presentation skills, with the ability to translate complex technical concepts into business-relevant insights
•    Bachelor’s degree in computer science, Computer Engineering, or a related discipline

Additional Advantage
•    Master’s degree in Analytics or Business Administration
•    Professional certifications (Azure, Data Engineering, Architecture)
•    Bilingual (English + French or other African language)
•    Experience working in pan-African or multi-country environments

Skills, Capabilities & Direct attributes 
•    Strong solution design and architectural thinking capability, with the ability to translate complex business requirements into scalable, fit-for-purpose technical solutions 
•    Proven ability to engage and collaborate effectively with stakeholders across business units, affiliates, and senior management, maintaining strong cross-functional relationships 
•    Demonstrated problem-solving capability, execution discipline, and delivery focus, with the ability to manage multiple priorities, projects, and deadlines across distributed teams and regions 
•    High level of attention to detail, with strong organizational, time management, and issue resolution skills 
•    Effective communication and presentation skills, with the ability to clearly articulate technical concepts to both technical and non-technical audiences 
•    Strong sense of innovation and continuous improvement, coupled with a proactive and self-driven approach to learning and capability development 
•    Ability to work with sensitive and confidential data, maintaining the highest standards of integrity and data protection 
•    Strong analytical mindset, with demonstrated ability to derive meaningful business insights from large and complex datasets