Data Engineer – Manager – AI & Data at Deloitte

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.

Qualifications

• 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