Abidakun Abisoye
Data Engineer @Relay
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WORK HISTORY
Data Engineer @Relay
Architected and deployed an in-house event schema management and data pipeline platform, replacing Segment and delivering cost savings while improving data governance and ownership- Designed an API-driven schema contracting system to automate event validation, lifecycle management, and schema evolution across product teams- Built CI/CD tooling to generate and distribute AJV validators and Pydantic models, enabling consistent event enforcement across data services- Implemented Dagster-orchestrated batch and real-time event ingestion pipelines, loading curated data into Snowflake with optimized S3 partitioning for performance and discoverability- Established end-to-end observability and SLAs using Datadog, and partnered cross-functionally with Product, Analytics, and Engineering to standardize event definitions and analytics foundations.
EDUCATION
Udacity
Nanodegree, Data Engineering
University of Aberdeen
MSc(Econs), Petroleum, Energy Economics and Finance
University of Port Harcourt
Master of Engineering - MEng, Subsea Engineering
University of Aberdeen
PhD Computing Science - Deep Learning application to Causal Inference in Time Series , Computing Science - Deep Learning application to Causal Inference in Time Series
University of Ibadan
Bachelor of Science (B.Sc.), Petroleum Engineering
SKILLS
ABOUT ABIDAKUN ABISOYE
Hi! I\'m Abisoye Abidakun.I’m a Data Engineer focused on designing, building, and operating large-scale, reliable data platforms that power product analytics, experimentation, and business-critical decision-making.My work centers on event-driven and distributed data systems, where I’ve owned end-to-end architecture, from schema design and data ingestion to transformation, governance, and observability, across batch and real-time workloads. I’ve led initiatives to replace third-party vendor solutions with in-house platforms, significantly reducing cost while improving data quality, ownership, and flexibility at scale.I have deep experience building cloud-native data platforms on AWS and GCP, working with modern data warehouses (Snowflake, BigQuery), orchestration frameworks (Airflow, Dagster), and transformation layers (dbt). I care strongly about data correctness, schema evolution, monitoring, and operational excellence, and I design systems with failure modes, SLAs, and long-term maintainability in mind.Beyond the technical work, I regularly partner with Product, Engineering, Finance, and Analytics teams to define trusted metrics, unblock product launches, and translate ambiguous requirements into well-scoped, scalable data solutions. I’ve driven projects that improved customer acquisition efficiency, accelerated analytics delivery, and enabled data to be embedded directly into operational workflows.I enjoy tackling complex systems problems, mentoring engineers, and working in environments where engineering rigor, autonomy, and impact at scale matter.
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