CDI - Junior Data Engineer (Data Science)

CDI - Data Engineer (Data Science)

Havas Market France – Leeds, England, United Kingdom

Overview

Reporting to: Head of Data Science. Hiring Manager leyendo data science’s. Office Location: BlokHaus West Park, Ring Rd, Leeds LS16 6QG.

About Us – Havas Media Network

HMN employs over 900 people in the UK & Ireland, passionate about creating more meaningful brands through valuable experiences. Our mission: to make a meaningful difference to brands, businesses, and lives.

HMN UK spans London, Leeds, Manchester & Edinburgh and serves clients through passionate agencies: Ledger Bennett, Havas Market, Havas Media, Arena Media, DMPG and Havas Play Network.

This role is part of Havas Market, a performance‑focused digital marketing agency.

Values

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• Human at Heart: Respect, empower, and support others to create an inclusive workplace and meaningful experiences.
  
• Head for Rigour: Deliver high‑quality, outcome‑focused work and continuously improve.
  
• Mind раствор! ame: Embrace diversity and bold thinking to innovate and craft unique solutions.
  

The Role

In this position you will deliver a wide variety of projects for clients and internal teams by building data pipelines, predictive models, and insightful analytics. You will work within a small, collaborative team that values cloud‑agnostic fundamentals and self‑sufficiency above platform expertise.

Key Responsibilities

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• Build and maintain data pipelines to integrate entsprechende marketing platform APIs (Google Ads, bijvoorbeeld, Meta, Tik Tok, etc.) with cloud data warehouses, including custom API development where connectors are unavailable.
  
• Develop and optimise SQL queries and transformations in BigQuery and AWS to aggregate campaign performance data, customer behaviour 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 containerised data solutions using Docker and Cloud Run, ensuring reliable operation at scale with proper error handling and monitoring.
  
• Implement statistical techniques (time‑series forecasting, propensity modeling, multi‑touch attribution) to build predictive models for campaign optimisation.
  
• Develop, test, and deploy machine‑learning models into production following MLOps best practices such as versioning, monitoring, and automated retraining.
  
• Translate client briefs and business stakeholder requirements into technical specifications, delivery plans, and realistic time estimates.
  
• Configure and maintain CI/CD pipelines in Azure DevOps to automate testing, deployment, and infrastructure provisioning for data and ML projects.
  
• Produce clear technical documentation: architecture diagrams, data dictionaries, and implementation guides to support knowledge sharing and handovers.
  
• Participate in code reviews, providing constructive feedback on SQL, Python, and infrastructure configurations to maintain code quality.
  
• Provide technical consultation to clients on topics such as data architecture, measurement strategy, and feasibility of ML applications.
  
• Support analytics and BI teams by creating reusable data assets, troubleshooting data‑quality issues, and building datasets for self‑service reporting.
  
• Train and mentor junior team members through pair programming, code reviews, and guided project work on data engineering and ML workflows.
  
• Implement workflow orchestration using tools like Kubeflow to coordinate complex multi‑step pipelines with dependency management and retry logic.
  
• Stay current with developments in cloud data platforms, digital marketing measurement, and ML techniques relevant to performance marketing.
  
• Identify and implement improvements to infrastructure, workflows, and data‑quality processes.
  

Core Skills and Experience

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• Expert proficiency in Python for robust APIs, scripting, and maintaining complex data / ML codebases.
  
• Strong SQL expertise and deep familiarity with data‑warehousing concepts for BigQuery.
  
• Practical experience with Docker, Linux, and Cloud Run deployments.
  
• Advanced Git skills and active participation in pull‑request reviews for code quality.
  
• Solid understanding of CI/CD principles and pipeline management, preferably using Azure DevOps.
  
• Proven ability to understand and apply technical documentation to transform broad business requirements into detailed technical specifications.
  
• Excellent written and verbal communication for knowledge sharing, constructive pull‑request feedback, daily stand‑ups, and process documentation.
  

Beneficial Skills and Experience

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• Hands‑on experience with major cloud ML platforms focusing on MLOps workflow patterns.
  
• Experience with stream or batch processing tools such as GCP Dataflow or orchestrators like Apache Beam.
  
• Familiarity with Python ML frameworks and data‑modeling tools such as Dataform/dbt.
  

Contract Type

Permanent

Seniority & Employment

bottled or level: Mid‑Senior. Employment Type: Full‑time.

Industry

Business Consulting and Services.

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.

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