Data Engineer (Data Science)

Havas Market
Leeds
2 days ago
Create job alert

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:BlokHausWest Park, Ring Rd, Leeds LS16 6QG

About Us – Havas Media Network

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 willbe 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.

The Role

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.

Key Responsibilities

Build and maintain data pipelines to integrate marketing platform APIs (Google Ads, Meta, TikTok, etc.) with cloud data warehouses, including custom API development where platform connectors are unavailable

Develop and optimize SQL queries and data transformations inBigQueryand AWS to aggregate campaign performance data,customerbehaviormetrics, and attribution modelsfor 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 andCloud Run, ensuring pipelines run reliably at scale with appropriate error handling and monitoring

Implement statistical techniques such as time series forecasting, propensitymodeling, or multi-touch attribution to build predictive models for client campaign optimization

Develop,test, and deploy machine learning models into production environments with MLOps best practices including versioning, monitoring, andautomated retrainingworkflows

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 DevOps 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 Intelligence teams by creating reusable data assets, troubleshooting data quality issues, and building datasets that enable self-service reporting

Train and mentor junior team members through pair programming, code review feedback, and guided project work on data engineering and ML workflows

Implement workflow orchestration using tools likeKubeflowto coordinate complex multi-step data pipelines with appropriate dependency management and retry logic

Stay current with developments in cloud data platforms, digital marketing measurement, and ML techniques relevant to performance marketing optimization

Identify and implement improvements to team infrastructure, development workflows, and data quality processes

CoreSkills andExperienceWeAreLookingFor:

Expert-level proficiency in Python for building robust APIs, scripting, and maintaining complex data/ML codebases.

Strong SQL expertise and deep familiarity with data warehousing concepts relevant to toolslikeBigQuery.

Practical experience with Docker and a firm grasp of the Linux to manage localdevcontainers, servers,and Cloud Run deployments.

Advanced Git proficiency and active experience participating in PRreviews to maintain code quality.

Solid understanding of CI/CD principles and practical experience defining or managing pipelines, preferably using a tool like Azure DevOps.

Proven ability to quickly read, understand, and apply technical documentation to translate broad business requirements into precise technical specifications.

Excellent written and verbal communication skills for proactive knowledge sharing, constructive PR feedback, participating in daily standups, anddocumenting processes.

Beneficial skills and experience to have:

Hands-on experience with any major cloud ML platform,focusing onMLOpsworkflow patterns.

Practical experience with stream or batch processing tools like GCP Dataflow or general orchestrators likeApache Beam.

Familiarity with Python ML frameworks or datamodelingtools likeDataform/dbt.

Familiarity with the structure and core offerings of GCPor AWS.

Contract Type:Permanent

Here at Havas across the group we pride ourselves on being committed to offering equal opportunities to all potential employees and have zero tolerance for discrimination. We are an equal opportunity employer and welcome applicants irrespective of age, sex, race, ethnicity, disability and other factors that have no bearing on an individual’s ability to perform their job.

#LI-PH1

Contract Type :

Permanent

Here at Havas across the group we pride ourselves on being committed to offering equal opportunities to all potential employees and have zero tolerance for discrimination. We are an equal opportunity employer and welcome applicants irrespective of age, sex, race, ethnicity, disability and other factors that have no bearing on an individual’s ability to perform their job.

Related Jobs

View all jobs

Data Engineer (Data Science)

Data Science & ML Engineer (Azure Data Pipelines)

Data/Machine Learning Ops Engineer

Senior DataOps Engineer

Senior Data Science Engineer

Senior Data Science Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.

AI Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we head into 2026, the AI hiring market in the UK is going through one of its biggest shake-ups yet. Economic conditions are still tight, some employers are cutting headcount, & AI itself is automating whole chunks of work. At the same time, demand for strong AI talent is still rising, salaries for in-demand skills remain high, & new roles are emerging around AI safety, governance & automation. Whether you are an AI job seeker planning your next move or a recruiter trying to build teams in a volatile market, understanding the key AI hiring trends for 2026 will help you stay ahead. This guide breaks down the most important trends to watch, what they mean in practice, & how to adapt – with practical actions for both candidates & hiring teams.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.