Data Engineer | End-to-End Data Systems that turn raw data into production AI.
I design and ship data infrastructure across ingestion, transformation, orchestration, and serving. My work focuses on streaming architectures, data quality enforcement, and cloud-native deployment. Three years plus of hands-on experience delivering production pipelines for analytics and ML.
Background in Applied Geophysics. Working with large earth datasets taught me that clean, validated, well-structured data is the foundation of every downstream decision. That path led me into data engineering.
Lagos, Nigeria | Open to remote roles
- Real-Time Fraud Detection Platform | Kafka and Flink windowed aggregations, Feast feature store, XGBoost and River ensemble, sub-50ms scoring on EKS
- BESS Optimization and Trading Platform | Real-time battery telemetry and market price ingestion, Flink stream processing, LP/MILP/MPC dispatch optimization, FastAPI serving
End-to-end analytics platform for a live prediction market. Snapshot-aware pipeline processing 300k+ records with automated daily ETL, clustering and PCA models, and two live ML inference models served through a 10-page Streamlit dashboard.
Python | PostgreSQL | GitHub Actions | Streamlit | scikit-learn
Contributor analytics system with time-series schema design in Neon PostgreSQL. Automated ingestion, validation, and persistence with database-level constraints.
Python | Neon PostgreSQL | GitHub Actions | Streamlit
Data platform ingesting Nigerian grid load, demand, outage, and solar resource data. XGBoost grid instability prediction, BESS dispatch optimization using linear programming, and mini-grid viability scoring.
Python | dbt | XGBoost | PuLP | Streamlit | PostgreSQL
Languages
Python | SQL | Bash | TypeScript (working)
Data Engineering
Apache Kafka | Apache Flink | Apache Spark | dbt | Dagster | Airflow
Storage and Databases
PostgreSQL | TimescaleDB | Redis | Apache Iceberg | Delta Lake | S3 | ClickHouse
ML and Optimization
XGBoost | scikit-learn | River | PuLP + HiGHS | CasADi + IPOPT | MLflow | Feast
Backend and Serving
FastAPI | Streamlit | REST APIs | WebSockets
Cloud and Infrastructure
AWS (S3, EKS, MSK, Lambda, KMS) | Docker | Kubernetes | Terraform | Helm | ArgoCD
Data Quality and Governance
Great Expectations | Presidio | Lake Formation | OpenLineage | DataHub
Observability
Prometheus | Grafana | OpenTelemetry
- Real-time stream processing with Flink: windowing strategies, watermark handling, and state management for high-volume event streams
- MLOps for production systems: feature store patterns, online learning, and drift detection with River and ADWIN
- Cloud-native data infrastructure: Terraform modules, Kubernetes deployments on EKS, and GitOps workflows with ArgoCD
- Distributed optimization for energy systems: linear programming, mixed-integer programming, and model predictive control for battery dispatch
- Data contracts and governance at scale: schema enforcement, lineage tracking, and column-level access control across lakehouse architectures
I build data systems that run without me. If that is the kind of engineering you need, let's talk.