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AnaVation LLC
A global digital media company is seeking a Data Engineer to join its fast-paced, data-driven team in London. The role focuses on shaping data collection and activation across various functions. Responsibilities include building scalable data pipelines and optimizing infrastructure while ensuring data quality. The ideal candidate has strong skills in Python or Pyspark and experience with cloud technologies like GCP or AWS. This position is pivotal for revenue optimization and strategic insights.
We are currently looking for an Data Engineer to join our fast-paced, data-driven tech team within a global digital media environment. You’ll play a crucial role in shaping how the business collects, models, and activates data across multiple commercial and editorial functions. In this hands-on role, you will architect and build scalable data pipelines, optimise infrastructure, and deliver high-value insight tools that empower decision makers. The Data Engineer will work closely with commercial, product, and analytics teams, making this position vital to the organisation’s long-term data strategy.
As an Data Engineer, you’ll combine engineering, analytics, and product thinking to create a reliable, high-performing data ecosystem. You’ll have the opportunity to work with modern cloud technologies, large-scale datasets, and a business that truly values data as a strategic asset.
This role stands out because it sits at the intersection of engineering and commercial impact, your work directly supports revenue optimisation, global reporting, and critical business decisions.
If you would like to be considered for the role and feel you would be an ideal fit with our team then please send your CV to us by clicking on the Apply button below.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.