Data Engineer

Description:

In this role you will be part of Gemba’s Data & Analytics team where you will collaborate with cross-functional teams to gather and understand data requirements to continuously transform data pipelines serving Gemba’s own data products and client solutions covering a variety of different data sources.

You will be required to deliver high quality client solutions through efficient and effective practices that will allow data to be efficiently accessed for analysis and reporting purposes. This includes assisting in the design and implementation of data models and databases through to the development, and deployment of scalable data pipelines and ETL processes. This role is a great opportunity to deliver meaningful impact to clients by transforming their data architecture to drive positive commercial outcomes.

You will also be responsible for managing our internal Gemba Data Platform, including maintaining existing pipelines, enhancing the platform, and creating new data connections to a variety of data platforms. You will use the platform to leverage first and third-party data to continuously develop Gemba Data Products. You will at times be expected to work with senior stakeholders on client projects and so strong communication both written and verbal is important in this role.

Applicants are required to work in the office in London 4 days per week, with 1 day per week remote working from home.

About You

This key role requires a Data Engineer with 3+ years of experience (preferably with a keen interest in sport) with a focus on applying best practices in DevOps (such as CI/CD) in delivering data and analytics products and services. Possessing technical skills in Python and SQL, as well as knowledge of cloud technologies such as Google Cloud Platform (GCP), Azure or AWS is mandatory. Prior experience with cloud-based data stores, data orchestration tools, and analysis services will be highly regarded.

A good understanding of general business principles is essential, with relevant tertiary qualifications in economics, marketing, computer science, statistics, engineering, or similar.

Essential skills and experience:

• Advanced data manipulation and processing skills
• Experience with data orchestration tools such as dbt or Airflow
• Good understanding with data warehousing concepts and technologies
• Strong understanding of database architecture
• Ability to work effectively in a fast-paced, dynamic environment and manage multiple priorities
• Strong written and verbal communication skills