We have partnered with a large, diversified conglomerate to hire an AI Manager with a Data Engineering focus. This is a hands-on technical leadership role sitting at the intersection of data infrastructure and AI delivery.
The business is moving fast on its AI agenda and needs someone who understands that the quality of what gets deployed is only ever as good as the data that powers it. You will own the data engineering workstream within a cross-functional AI team, building the pipelines, platforms and architecture that make production AI systems possible.
This role suits a technically strong engineer who has grown into delivery leadership and wants to operate at the centre of a genuinely ambitious AI programme.
About the role:
- Design and build scalable, production-grade data pipelines and infrastructure that directly support AI and ML systems across the Group
- Translate business use cases into clean, well-architected technical solutions across both batch and streaming data environments
- Own data platform development across cloud environments, ensuring reliability, performance and scalability at enterprise scale
- Develop APIs, workflows and integrations that connect data infrastructure to AI and ML systems
- Lead delivery across small engineering pods, maintaining pace, quality and clear accountability
- Ensure all solutions meet production readiness standards including monitoring, observability and fault tolerance
About you:
- Strong hands-on experience building and maintaining data pipelines using ETL and ELT patterns in production environments
- Proficiency with cloud data platforms such as Snowflake, BigQuery or Redshift
- Experience with both batch and streaming processing frameworks such as Apache Spark, Kafka or equivalent
- Strong SQL and Python skills, with an understanding of software engineering principles applied to data
- Experience designing data architecture that supports AI and ML systems, including feature stores, data lakes and semantic layers
- Comfortable leading engineering teams and managing delivery across multiple workstreams