Data Engineer

About BlueCo Data

BlueCo Data is a cutting-edge sports analytics and technology group focused on building advanced data and modelling capabilities for elite football organisations, including Chelsea FC. Our work supports decision-making across areas such as player recruitment, squad construction, performance analysis, and long-term football strategy. We combine modern data engineering, machine learning, and applied football expertise to build systems and models that deliver actionable insights to drive success at the highest levels of competition. Our team includes data scientists, engineers, analysts, and football experts working together in a highly collaborative environment where ideas move quickly from concept to real-world application.

Role Overview

We are looking for an experienced Data Engineer to play a key role in building and maintaining the data foundations that support analytics, modelling, and decision-making across partner clubs. In this role, you will develop reliable, scalable data systems that process football data from multiple sources including event data, tracking data, player information, and scouting reports. Working alongside data scientists, analysts, and software engineers, you will ensure that models and insights are built on clean, well-structured, and dependable data pipelines. If you are passionate about data engineering, software design, and football — and want your work to impact real-world football decisions — we would love to hear from you.

Key Responsibilities

· Design, develop, and maintain data ingestion and transformation pipelines for structured and unstructured football data

· Build and maintain robust data models and storage layers that support analytics and downstream modelling

· Work closely with data scientists and engineers to support downstream model deployment workflows and ML systems

· Monitor pipeline reliability and performance, identify bottlenecks, and improve efficiency over time

· Implement data quality checks, monitoring, and documentation to ensure trust in downstream outputs

· Ensure appropriate data security, access control, and governance standards are upheld

· Contribute to shared tooling, patterns, and best practices that improve the overall reliability of the data stack

Technical Skills & Experience

Required

· Degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience

· Extensive experience in data engineering or a similar role

· Strong database design and development skills

· Proficiency in Python for data engineering tasks

· Experience working in cloud data environments (Azure preferred)

· Strong software engineering practices, including designing modular and maintainable data systems, defining clear abstractions, developing reusable components, applying testing strategies (unit, integration, and data quality checks), participating in code reviews, and operating data systems in production

Desirable

· Familiarity with MLOps concepts and best practices, including supporting model deployment, versioning, and monitoring in collaboration with ML engineers

· Experience using AI/LLM-assisted development tools, with a focus on effective planning and problem decomposition, producing clear and maintainable code, documenting design decisions, and exercising strong judgment on when and how LLMs should be used to accelerate development

· Experience documenting and explaining data architectures, pipeline designs, and system trade-offs to non-technical or semi-technical stakeholders

· Experience working with unstructured or semi-structured data (e.g. text, reports, JSON)

Soft Skills & Mindset

· Proactive and self-driven, with a strong sense of ownership over assigned systems and domains

· Eager to learn and continuously improve technical and analytical approaches

· Curious about new tools and methodologies, with sound judgment about when to adopt them

· Passionate about football or sports, and motivated by the opportunity to apply data in a real decision-making environment