Nigerian Senior Data Engineer Needed
Budget: €6 – €12 EUR
I’m building a new web-based platform whose core value is clear, interactive data-visualization. To get there I need an experienced Nigerian software engineer who is equally at home designing back-end services and shaping the data that feeds them.
Your first mandate will be to architect and code the full data pipeline—from ingestion through transformation to storage—so that the front-end team always has clean, query-ready information. You’ll also dive into exploratory and diagnostic analysis, helping us uncover trends that inform product decisions and power the visual stories we show users.
The stack is flexible, but you should be comfortable with modern data-engineering tools (think Python or Scala for ETL, SQL-based warehouses, stream processing frameworks, containerised deployments, and cloud services such as AWS or GCP). On the web side we are leaning toward a REST-or GraphQL-driven API that feeds a JavaScript visualisation layer. If you have a preferred alternative that achieves the same performance and scalability goals, I’m open to it.
By the end of our first milestone I expect:
• An automated, version-controlled pipeline that ingests raw data, applies the agreed transformations, and lands it in an analytics-ready warehouse.
• A lightweight web service that exposes that data to the front-end, complete with sample endpoints powering at least one interactive chart.
• Clear documentation and run-books so other engineers—and eventually data analysts—can extend what you’ve built.
If you’re based in Nigeria and have senior-level experience in both software engineering and data engineering, let’s talk.
Your first mandate will be to architect and code the full data pipeline—from ingestion through transformation to storage—so that the front-end team always has clean, query-ready information. You’ll also dive into exploratory and diagnostic analysis, helping us uncover trends that inform product decisions and power the visual stories we show users.
The stack is flexible, but you should be comfortable with modern data-engineering tools (think Python or Scala for ETL, SQL-based warehouses, stream processing frameworks, containerised deployments, and cloud services such as AWS or GCP). On the web side we are leaning toward a REST-or GraphQL-driven API that feeds a JavaScript visualisation layer. If you have a preferred alternative that achieves the same performance and scalability goals, I’m open to it.
By the end of our first milestone I expect:
• An automated, version-controlled pipeline that ingests raw data, applies the agreed transformations, and lands it in an analytics-ready warehouse.
• A lightweight web service that exposes that data to the front-end, complete with sample endpoints powering at least one interactive chart.
• Clear documentation and run-books so other engineers—and eventually data analysts—can extend what you’ve built.
If you’re based in Nigeria and have senior-level experience in both software engineering and data engineering, let’s talk.