Data Engineer

Data Science Festival; Greater London; Hybrid; GBP 60,000 - GBP 80,000; Full time

Job summary

A global digital media company is searching for a Data Engineer. In this role, you will shape how business data is collected and utilised while optimising data architectures and delivering tools for decision-makers. Responsibilities include building ETL/ELT data pipelines, managing data infrastructures, and collaborating with various teams to ensure data quality and drive insights. The ideal candidate will have strong Python skills, experience with GCP and AWS, and an understanding of Big Data environments.

Responsibilities

• Build, operate, and optimise end‑to‑end ETL/ELT data pipelines.
• Develop scalable data models supporting commercial functions.
• Manage complex data infrastructure processing Big Data.
• Create and enhance interactive dashboards for KPI decision‑making.
• Ensure accuracy and reliability across core datasets.
• Analyse performance and provide actionable insights.
• Collaborate with Operations, Sales, Marketing, and Finance teams.
• Support strategic projects with data modelling and insights.

Skills

Python

Pyspark

GCP (BigQuery, Compute Engine, Kubernetes)

AWS (Redshift, EC2)

ETL/ELT pipelines

APIs

SFTP integrations

Data modeling

Big Data environments

Analytical skills

Problem-solving skills

Project management

Job description

Data Engineer

Contract – £550 – £650pd
Location: London – 1 day per week

We are currently looking for a 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.

The Opportunity

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.

Key responsibilities include:

• Building, operating, and optimising end‑to‑end ETL/ELT data pipelines using APIs, SFTP, and containerised orchestration tools.
• Developing scalable and well‑structured data models that support commercial, programmatic, and affiliate revenue functions.
• Managing and improving complex data infrastructure that processes high‑volume, multi‑source Big Data.
• Creating, maintaining, and enhancing interactive dashboards that drive KPI‑focused decision‑making.
• Owning data quality, ensuring accuracy, consistency, and reliability across all core datasets.
• Analysing campaign, monetisation, and platform performance and providing actionable insights.
• Collaborating with Operations, Sales, Marketing, Finance, and Senior Analytics teams.
• Supporting strategic projects with advanced data modelling and insight generation.

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.

Skills and Experience

• Strong Python and or Pyspark
• Experience with cloud technologies such as GCP (BigQuery, Compute Engine, Kubernetes) and AWS (Redshift, EC2).
• Experience building ETL/ELT pipelines and working with APIs or SFTP integrations.
• Understanding of data modelling, warehousing, and Big Data environments.
• Strong analytical and creative problem‑solving skills.
• Ability to manage projects and collaborate effectively in a team.
• Experience creating util packages in Python

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.