Data Engineer – Manager – AI & Data

As a Data Engineering Manager, you will lead the design, build, and scale of enterprise-grade data infrastructure and pipelines to power advanced analytics, AI solutions, and AI transformations across Tier-1 clients on the African continent. You will work at the intersection of business strategy and technical delivery, guiding multidisciplinary teams to enable data-driven decision-making and measurable business impact.

You will be responsible for:

• Architecting scalable, secure, and high-performance data platforms
• Leading the design and development of robust ingestion, transformation, and governance pipelines
• Managing project timelines and deliverables across diverse industry engagements
• Coaching data engineers and analysts to deliver client-ready solutions
• Collaborating with AI/ML specialists, solution managers, and client stakeholders to translate strategic needs into modern data capabilities
• Lead and own data engineering workstreams across AI transformation, analytics modernisation, and digital core rebuilds
• Design and implement data pipelines using modern architectures (e.g., Delta Lake, Data Mesh, Data Lakehouse)
• Drive data modelling, data quality, and metadata management best practices aligned to business KPIs.
• Build, manage, and scale cloud-native data infrastructure (e.g., on AWS, GCP, Azure)
• Mentor junior engineers, oversee code reviews, and ensure delivery quality to tier-1 consulting standards.
• Translate business and industry requirements into scalable data engineering solutions
• Partner with AI, strategy, and business consulting teams to deliver end-to-end data value realisation.

• A bachelor’s degree in computer science, software engineering, or a related discipline with a minimum of Second Class Upper/Upper Credit division.
• Have a minimum of five credits in WASSCE Ordinary Level/NECO subjects or acceptable equivalent examination, including Mathematics and English Language in one sitting only.
• Minimum of 8 years of experience in data engineering, with at least 2 years in a team leadership or technical management role
• Proficient in building modern ETL/ELT pipelines using tools like Apache Spark, DBT, Kafka, Airflow
• Strong programming skills in Python and SQL (Scala/Java a plus)
• Deep experience with cloud data ecosystems (e.g., AWS Redshift/Glue, GCP BigQuery/Dataflow, Azure Synapse)
• Strong understanding of data warehousing, data lakes, streaming, and batch architecture
• Experience with CI/CD for data, testing frameworks, and infrastructure-as-code (Terraform, etc.)
• Familiarity with data governance and security frameworks in regulated industries (e.g., FSI, healthcare)
• Previous experience in a top-tier consulting environment or client-facing data role
• Exposure to AI/ML deployment pipelines, MLOps, or analytics.
• Experience in delivering data modernization programs at enterprise scale

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Application deadline: Friday, 23 January 2025.

At Deloitte, we want everyone to feel they can be themselves and to thrive at work—in every country, in everything we do, every day. We aim to create a workplace where everyone is treated fairly and with respect, including reasonable accommodation for persons with disabilities. We seek to create and leverage our diverse workforce to build an inclusive environment across the African continent.

We actively support the inclusion of people with disabilities and embrace neurodiversity in the workplace. We recognise and value the unique strengths that neurodivergent individuals bring, and we are committed to creating an environment where everyone can thrive.

If you require reasonable accommodations in relation to your disability and neurodiverse needs during the recruitment process, please let us know. We are happy to make adjustments to suit your individual needs.

Note: The list of tasks / duties and responsibilities contained in this document is not necessarily exhaustive.  Deloitte may ask the employee to carry out additional duties or responsibilities, which may fall reasonably within the ambit of the role profile, depending on operational requirements.

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