Analytics Engineer

· Maintain and proactively develop data models & products: with a focus on reusable data assets that can deliver value across multiple use cases

· Work with the Data Engineering and Analytics team: to structure datasets that can be used to build data products and other use cases

· Monitoring, Testing and data quality: Building rigorous automated checks against datasets to ensure freshness and consistency

· Documentation - Enabling easy understanding of models and the fields within them so that the users of the data can quickly understand which dataset they should use to answer a particular question

· Identify Opportunities: Work closely with colleagues to identify key strategic opportunities where Analytics Engineering techniques can be used to improve decision making and project streams

· Be a subject matter expert for Analytics Engineering: advising on best practices during scoping phase of projects with cross functional teams

What You'll Love About This Role

• Think Big: We've got some of the largest and most diverse data sets in UK media - with scale that continues to grow. You'll play a role in harnessing the value in that data.
• Own It: You'll be doing this by gaining expertise in one of our data domains
• Keep it Simple: With a focus on reusability of data sets and models to support multiple use cases
• Better Together: You'll be working in a team with kind, supportive people that look out for you and help you to do the best work that you can. We put a lot of energy into our team culture and ensuring that everyone is fulfilled with their work.

What Success Looks Like

In your first few months, you'll have:

• Learnt how the team operates and uses technologies such as Snowflake, dbt, Airflow
• Built a clear understanding of the strategic direction of Data and Analytics at Global as well as how these feed into the wider business' goals
• Integrated within Agile team ceremonies such as daily stand ups, retrospectives and backlog refinements
• Started to establish a strong understanding of Global's datasets and their use in the business

• Analytics Engineering Skills: previous experience in an Analytics Engineering position

• Data Modelling: Proven ability to design and maintain scalable, well-documented data models that enable multiple use cases.
• Data Curation Tools: e.g. dbt or Python for data manipulation and transformation
• SQL: ability to write complex SQL that runs efficiently especially on cloud data platforms (E.g. Snowflake)
• Orchestration: Proficiency with orchestration tools (E.g. Airflow)
• DataOps: Experience with git & CI/CD, and appreciation of FinOps
• Cloud: Proficiency with cloud services (ideally AWS)

• Agile ways of working: Understanding of Agile methodologies and experience of using Jira
• Can do attitude: Proactive, problem-solving attitude with strong attention to detail
• To be organised: Strong organisational skills with the ability to work both individually or part of a team and an eye for detail and quality
• Great communication: An ability to break down and explain sophisticated technical concepts to business end users
• A growth mindset: A proven ability to learn new skills and pick up new technologies quickly