We are hiring a Data Engineer for a data, services, and software company that partners with governments, cities, fitness operators, and sports bodies to maximise return on investment in sport, leisure,e and physical activity programmes.

The Data Engineer will play a key role in building and maintaining reliable data pipelines and integrations that feed InsightOS. This position supports the internalisation of data engineering capabilities previously handled externally, enabling stronger control over data quality, reliability, and performance. Working closely with Backend, GIS, and Infrastructure colleagues, you will help design scalable ingestion and transformation workflows that underpin our predictive analytics platform.

Key Responsibilities:

• Develop and maintain ETL/ELT pipelines to integrate data from multiple internal and external sources into InsightOS.
• Support API-driven data ingestion and transformation workflows, including monitoring and troubleshooting.
• Collaborate with Backend, GIS, and Infrastructure teams to ensure consistent, reliable data availability for product and internal stakeholders.
• Improve data quality, performance, and documentation across pipelines and integrations.
• Contribute to defining data models, ingestion strategies, and best practices for transformation and validation.
• Ensure alignment with 4GLOBAL’s data governance, reliability, and security standards.
• Provide day-to-day technical leadership,including mentoring/supporting more junior employee’s, contributing to delivery planning, and helping to drive best practice across the team.

Skillset Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Data Science, Statistics, Mathematics, or a related field (or equivalent practical experience).
• A minimum of 5 years’ experience in data engineering (or closely related roles), with demonstrable ownership of production-grade pipelines and integrations.
• Familiarity with cloud environments and data infrastructure concepts (e.g., storage, compute, orchestration, monitoring). can we specifically say (AWS)
• Strong SQL fundamentals with experience querying and transforming complex datasets.
• Hands-on experience with Python (or a similar language/tooling) for data processing and automation.
• Solid understanding of ETL/ELT concepts, data modelling, and data pipeline design patterns.
• Experience ingesting data via APIs (authentication, rate limits, data normalisation, error handling).
• Familiarity with cloud environments and data infrastructure concepts (e.g., storage, compute, orchestration, monitoring).
• Strong problem-solving skills and the ability to diagnose data issues and optimise pipeline performance.
• Management/leadership experience, such as mentoring, coaching, leading workstreams, or line management responsibility within an engineering or data context.
• Clear communication skills and comfort working cross-functionally in a fast-moving environment.
• Fluent English (spoken and written) is essential.
• A passion for sports, with an understanding of sports participation trends and concepts, is desirable.