Data Engineer; Data Science

Agency : Havas Market

Job Description : The Analyst Expert is responsible for placing data at the heart of our operations. S/He conducts cross analysis of complex data to monitor and optimize the performance of the marketing strategy for clients.

Data Engineer ( Data Science )

Reporting To :
Head of Data Science

Hiring Manager:
Head of Data Science

Office

Location:

Blok Haus West Park, Ring Rd, Leeds LS16 6QG

Havas Media Network (HMN) employees over 900 people in the UK & Ireland. We are passionate about helping our clients create more Meaningful Brands through the creation and delivery of more valuable experiences. Our Havas mission:
To make a meaningful difference to the brands, the businesses and the lives of the people we work with.

HMN UK spans London, Leeds, Manchester & Edinburgh, servicing our clients brilliantly through our agencies including Ledger Bennett, Havas Market, Havas Media, Arena Media, DMPG and Havas Play Network.

This role will be part of Havas Market, our performance-focused digital marketing agency.

Our values shape the way we work and define what we expect from our people:

• Human at Heart:
  You will respect, empower, and support others, fostering an inclusive workplace and creating meaningful experiences.
• Head for Rigour:
  You will take pride in delivering high‑quality, outcome‑focused work and continually strive for improvement.
• Mind for Flair:
  You will embrace diversity and bold thinking to innovate and craft brilliant, unique solutions.

These behaviours are integral to our culture and essential for delivering impactful work for our clients and colleagues.

In this position, you’ll play a vital role in delivering a wide variety of projects for our clients and internal teams. You’ll be responsible for creating solutions to a range of problems – from bringing data together from multiple sources into centralised datasets, to building predictive models to drive optimisation of our clients’ digital marketing.

We are a small, highly collaborative team, and we value cloud‑agnostic technical fundamentals and self‑sufficiency above specific platform expertise. The following requirements reflect the skills needed to contribute immediately and integrate smoothly with our existing workflow.

• Build and maintain data pipelines to integrate marketing platform APIs (Google Ads, Meta, Tik Tok, etc.) with cloud data warehouses, including custom API development where platform connectors are unavailable
• Develop and optimize SQL queries and data transformations in Big Query and AWS to aggregate campaign performance data, customer behavior metrics, and attribution models for reporting and analysis
• Design and implement data models that combine first‑party customer data with marketing performance data to enable cross‑channel analysis and audience segmentation
• Deploy containerized data solutions using Docker and Cloud Run, ensuring pipelines run reliably at scale with appropriate error handling and monitoring
• Implement statistical techniques such as time series forecasting, propensity modelling, or multi‑touch attribution to build predictive models for client campaign optimisation
• Develop, test, and deploy machine learning models into production environments with MLOps best practices including versioning, monitoring, and automated retraining workflows
• Translate client briefs and business stakeholder requirements into detailed technical specifications, delivery plans, and accurate time estimates
• Configure and maintain CI/CD pipelines in Azure Dev Ops to automate testing, deployment, and infrastructure provisioning for data and ML projects
• Create clear technical documentation including architecture diagrams, data dictionaries, and implementation guides to enable team knowledge sharing and project handovers
• Participate actively in code reviews, providing constructive feedback on SQL queries, Python code, and infrastructure configurations to maintain team code quality standards
• Provide technical consultation to clients on topics such as data architecture design, measurement strategy, and the feasibility of proposed ML applications
• Support Analytics and Business…