Junior Data Engineer

OTA Recruitment; England; Hybrid; GBP 40,000 - 55,000; Full time

Job summary

A specialized sports analytics firm is seeking a Data Engineer to design and optimize analytics workflows. This role requires proficiency in SQL and Python for data modeling and transformation, along with experience in cloud-based platforms. The ideal candidate will contribute to data quality and visualizations to support decision-making across the business. Ideal for someone with 1+ years of experience and excellent communication skills.

Qualifications

• Competent in SQL and Python for data transformation and analytics.
• Understanding of data modelling concepts like star schema.
• 1+ year experience with relational databases and designing schemas.
• Ability to debug and optimize slow queries.
• Familiarity with AWS or cloud-based data services.
• Excellent communication skills for collaboration.
• Strong problem-solving and analytical mindset.
• Experience with visualization tools like Power BI.
• Experience structuring APIs with Django or Flask.
• Familiarity with distributed systems like Spark.
• Knowledge of TDD in data workflows.

Responsibilities

• Design and implement data models optimized for analytics.
• Develop and maintain ELT/ETL pipelines.
• Collaborate with analysts and data scientists.
• Optimize SQL queries and workflows.
• Ensure data quality and governance.
• Document testing and reproducibility in workflows.
• Work with cloud tools and services.
• Develop dashboards and analytics tools.

Skills

SQL

Python

Data modelling

Debugging slow queries

Cloud-based data platforms

Communication skills

Problem-solving

BI tools

API structuring

Distributed systems

Testing practices

Documentation

Job description

Data Engineer - sports analytics/betting

Salary £40k‑£55k (plus substantial bonus on top)

Location: London or Leeds (very relaxed about hybrid/remote working)

Company description

We are a proprietary sports pricing and product provider, specializing in the development of intricate, simulation‑driven pricing and risk systems that empower leading sports brands. As pioneers in player‑level, play‑by‑play simulations and forecasting, we deliver the group’s most advanced pricing and risk capabilities – particularly focused on the US market.

Job Description

The purpose of the data engineer is to design, build, and optimize data models and analytics workflows that enable accurate, timely, and actionable insights across the business. This role bridges the gap between data engineering and analytics, ensuring that data is transformed into well‑structured, reliable datasets for reporting, visualization, and advanced analytics. The role holder will focus on creating scalable, maintainable solutions that empower stakeholders to make data‑driven decisions efficiently.

Key responsibilities

• Design and implement data models optimized for analytics and reporting use cases.
• Develop and maintain ELT/ETL pipelines to transform raw data into curated datasets.
• Collaborate with analysts and data scientists to understand requirements and deliver high‑quality data products.
• Optimize SQL queries and workflows for performance and scalability.
• Ensure data quality, consistency, and governance across all analytics layers.
• Implement best practices for documentation, testing, and reproducibility in analytics workflows.
• Work with cloud‑based tools and services (e.g., AWS S3, Athena, ECS, CloudFormation, Lambdas, CloudWatch) to support analytics infrastructure.
• Contribute to the development of dashboards and self‑service analytics tools.

Qualifications

• Competent in SQL and Python for data transformation and analytics.
• Understanding of data modelling concepts (e.g., star schema, dimensional modelling).
• Experience (1+ year) working with relational databases and designing optimized schemas.
• Ability to debug and optimise slow queries and inefficient workflows.
• Familiarity with cloud‑based data platforms and services (AWS preferred).
• Excellent communication skills for collaborating with technical and non‑technical stakeholders.
• Strong problem‑solving and analytical mindset.
• Experience with BI tools (e.g., Power BI, Plotly/Dash) for visualisation.
• Experience structuring APIs – Django, Flask, FastAPI.
• Familiarity with distributed systems (e.g., Spark, Kafka) for large‑scale analytics.
• Knowledge of testing practices (e.g., TDD) in data workflows.
• Passion for clean, well‑documented systems and reproducibility.

Seniority level: Associate

Employment type: Full‑time

Job function: Information Technology