Job DescriptionSenior Data Engineer
Salary: £60-75k (plus very attractive bonus on top)
Location: London/Leeds (hybrid working or fully remote an option, if preferred)
*We are looking to fill 2 roles. Please only apply if you have a strong interest in sports analytics/betting, you will be asked questions on this*
Purpose of role:
We have an exciting opportunity for a Senior Data Engineer to join a rapidly expanding Sports Analytics company.
The purpose of the role is to architect, design, implement and maintain data infrastructure that facilitates data-driven decision making, innovation and operational efficiency while ensuring that the data pipeline is secure, reliable, and scalable. The role holder will build and maintain high-performance data systems that are foundational to driving business growth and success.
Experience and knowledge:
- Significant experience in building, maintaining, and scaling large-scale data systems.
- Knowledge of data privacy and security, including data encryption and masking techniques.
- Experience with data modelling and architecture design using tools and techniques.
Key responsibilities:
- Designing and implementing scalable data architectures and systems.
- Developing and maintaining ETL (Extract, Transform, Load) pipelines.
- Managing data storage, backup, and recovery mechanisms.
- Writing complex SQL queries to extract data for analysis.
- Developing and implementing data security.
- Mentoring and coaching junior data engineers.
- Interfacing with clients, end users, and business stakeholders to provide transparency and receive guidance on projects, deliverables, and support.
Skills and competencies:
Essential:
- Understanding of data modelling concepts and be able to design data models that are optimised for different user cases.
- Good understanding of distributed systems such as Hadoop, Spark, and Kafka, and should be able to design and implement data pipelines that run on these systems.
- Write clean, efficient, and maintainable code.
- Proficient in writing complex SQL queries and have a deep understanding of database design principles.
- Ability to debug and optimize failing or slow data pipelines and queries.
- Systems integration experience: networking, data migrations, API integration and design.
- Enthusiasm for clean systems, including documentation, logging, and reproducibility.
- Experience with cloud platforms such as AWS, Google Cloud, or Azure and be able to design and implement scalable and secure data architectures.
- Excellent communication and teamwork skills that allow the engineer to collaborate with stakeholders.
- The ability to identify data quality issues and implement data quality rules and techniques to improve data accuracy.
- Interest in sports analytics and/or sports betting.
Desirable:
- Able to troubleshoot complex problems that arise during the Data Engineering process and be able to find effective solutions.
- Communicate complex technical concepts to non-technical stakeholders and be able to work effectively with cross-functional teams.
- An understanding of data governance and regulatory compliance requirements, such as GDPR and CCPA, and the ability to ensure that data pipelines meet these requirements.
- NoSQL experience such as MongoDB
- Coding in scripting languages such as Python