Available for new opportunities

Adeolu Adegboye

Data engineer building reliable pipelines, scalable infrastructure, and tools that turn raw data into insight.

About me

Building data systems that scale.

I'm a data engineer with a passion for building robust, high-throughput data systems. I specialise in designing ETL/ELT pipelines, orchestrating workflows with Airflow, and architecting cloud-native solutions on GCP.

My background spans data warehousing, stream processing, and MLOps — I enjoy the full spectrum from raw ingestion to serving clean, reliable data to stakeholders and ML models alike.

When I'm not wrangling data, I'm exploring new engineering tools, contributing to open-source projects, or writing about things I've learned along the way.

Projects

Things I've built

Real Time Fraud Detection Pipeline

A real-time fraud detection pipeline pipeline that processes a simulated transaction stream and flags suspicious activity using rule-based detection, deployed locally with Docker.

PythonKafkaSpark Structured StreamingPostgreSQL

Data Pipeline Orchestrator

End-to-end ELT pipeline using Airflow for orchestration, GCS as the data lake landing zone, and DBT for multi-layer transformations in BigQuery (raw -> staging -> mart), including automated data quality tests.

PythonAirflowDBTGCPBigQueryGCS

ML Feature Store

Centralised feature store for machine learning workflows, with versioned feature sets, point-in-time joins, and a REST API for serving.

PythonPostgreSQLFastAPIRedis

Cloud Infrastructure Automation

Terraform modules and CI/CD pipelines for provisioning GCP infrastructure, cutting deployment time by 70% across multiple environments.

TerraformGCPGitHub ActionsDocker

Contact

Let's connect

Whether it's a project, a role, or just a conversation about data — my inbox is always open.

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