Data Engineer: Scalable AI Data Pipelines

Global; Greater London; Sur place; GBP 65 000 - 95 000; Plein temps

Résumé du poste

Global is seeking a Data Engineer to design and build scalable data infrastructure powering AI-driven products and audience intelligence. The role focuses on batch and near real-time pipelines across ingestion, transformation and serving layers.

You will collaborate with Data Science, MLOps, Product and commercial teams, ensuring robust data quality, governance and clear documentation of data assets.

Qualifications

• Strong Python and SQL skills, with experience building production-grade data pipelines.
• Experience with modern data tools and cloud environments.
• Knowledge of CI/CD, testing, version control and IaC.
• Understanding of observability, validation and maintaining reliable data systems.
• Ability to translate business and data science needs into scalable solutions.

Responsabilités

• Data Platform & Pipeline Engineering (60%): Design, build and maintain scalable batch and near real-time pipelines across ingestion, transformation and serving layers.
• Platform Evolution & Engineering Excellence (20%): Shape data platform through best practices in architecture, tooling, CI/CD and infrastructure as code.
• Quality & Governance (10%): Implement data validation, testing, lineage and observability for high-quality datasets.
• Collaboration & Enablement (10%): Partner with Data Science, MLOps, Product and commercial teams to deliver production-ready data solutions.

Connaissances

Python

SQL

Data Pipelines

Data Platform

Outils

Snowflake

Airflow

dbt

AWS

Description du poste

Global is seeking a Data Engineer to design and build scalable data infrastructure powering AI-driven products and audience intelligence. The role focuses on batch and near real-time pipelines across ingestion, transformation and serving layers.

You will collaborate with Data Science, MLOps, Product and commercial teams, ensuring robust data quality, governance and clear documentation of data assets.