Data Platforms
Batch & streaming systems (Kafka, Spark)
Senior Data Engineer. Building platforms at scale.
Hello, I'm Tomiwa. I have 8+ years experience owning data infrastructures and AI automations end to end for enterprise SaaS, from architecture, build to observability across domains such as credit, payments, audit, marketing, learning & development, software consultancy, and professional services. I care about what is simple, what ships on time, what saves cost and what survives in production. At core for me, it's about value to users and stakeholders.
What I do
Core areas where I design and deliver production-ready data and AI systems.
Cloud Architecture
AWS, GCP, Azure scalable distributed systems
AI Systems
RAG pipelines, multi-agent workflows
Performance Engineering
Low-latency, high-throughput systems
Impact & Experience
Selected roles and outcomes across fintech, cloud data platforms, and AI projects.
- Design and maintain high-volume Airflow pipelines for financial reconciliation and settlement processing.
- Analyze large datasets with Python and SQL; optimize models and platform performance for speed, scalability, and cost on ClickHouse.
- Partner with cross-functional teams on data quality, reporting reliability, and business data needs.
- Built ETL for sentiment analysis on unstructured feedback using Airflow and Hugging Face BERT, with Tableau dashboards delivering ~98% accurate insights.
- Reduced pipeline breakage ~85% with a custom built Python CLI tool (N-ary trees, hash maps, Pandas) to manage model dependencies in Airflow as an alternative to dbt.
- Ran daily Redshift data-quality checks in Airflow; evaluated Snowflake with star-schema design; shipped a C++ ingestion engine ~25% faster than the legacy path.
- Hired by Andela as an independent contractor and placed with external clients such as Bravely.
- Delivered high-quality engineering outcomes leveraging cloud native data tools and best practices.
- Implemented Kafka Streams (Java) to ingest OpenTelemetry data into Druid on Azure; integrated Prometheus/Grafana for SLI/SLO visibility.
- Built Java Spring Boot REST services with Keycloak and PostgreSQL (Gradle, Flyway); JUnit coverage for REST and Kafka Streams paths.
- Delivered GCP Pub/Sub ingestion for marketing data (Salesforce, HubSpot, Albacross) through DataProc into BigQuery; Kimball-style OLAP with DBT and Looker for campaigns.
- Founded and lead engineering for a software practice that builds cloud data and AI infrastructure for client teams.
- Scope end-to-end delivery: solution architecture, implementation, and operations for analytics pipelines, data platforms, and related cloud workloads.
- Partner with organizations on technical strategy, hands-on build, and consulting as they modernize data and AI capabilities.
- Ran Spark (Scala) on EMR for MapReduce-style jobs exceeding 5B rows/day, improving turnaround time ~50%.
- Automated ML retraining end-to-end (Airflow on EKS, EMR, SageMaker, Slack alerts)—cut data-scientist manual effort from days to minutes.
- Built an S3 data lake with DMS, CDC, Spark, Glue, and Athena/Metabase—~70% improvement in cross-team accessibility and self-service analytics.
- Delivered ETL for audit and fraud analytics using Azure Data Factory, Synapse, T-SQL, and MS SQL Server on high-volume transactional data.
- Automated Oracle ingestion with SQL stored procedures; validation workflows (IDea & VBA) that sped Power BI reporting ~30%.
- Led NDPR, GDPR, and ISO 27001 data-governance reviews for telecom and banking clients; designed remediation to strengthen compliance and reduce audit risk.
Education
Certifications and continuous learning milestones from recent programs.
Tech stack
Tools and platforms I use to build scalable data, cloud, and AI solutions.
Languages:
Data & Streaming:
Cloud & Infrastructure:
Data Platforms:
AI / ML:
Personal Edge
The engineer behind the pipelines — and the person off the court.
How I work
Business-first engineering — solving real business problems is the priority. I make sure I lead or contribute to projects in ways that aligns with business needs.
Reliability & cost — I build low-maintenance systems with little overhead: efficient pipelines, lean operations, and architectures where changes are easy to apply safely.
Delivery & testing — speed matters, but not without quality. I treat delivery and testing as one discipline, not separate phases.
Leadership & collaboration — mentorship, clear ownership, and close partnership with product and data science when problems get ambiguous.
AI-assisted, evaluated — I use AI tools to move faster, with strong evaluation so output stays reliable. Problem-solving and accountability are how I show up on every project.
Beyond work
On the court & the couch — basketball pick-up games and videogames when I need a hard reset from the terminal.
Building in public — vibecoded games at /games; blogs and project notes at /work; always picking up new platform and ML tools (Udacity and side experiments).
Consulting — I also take on cloud data and platform projects through Tiptier.