Jobid=ffece582f063 (0.0996)
Build and operate the foundation of a global AI-powered data platform
Location: UK (preferred), Netherlands or Belgium
Are you a Data Platform Engineer who thrives on building reliable, scalable platforms for data and AI workloads? Do you enjoy operating at the intersection of platform engineering, DataOps and MLOps while enabling AI systems to run securely and at scale?
We are looking for a Data Platform Engineer (AI & ML Infrastructure) to take ownership of the reliability, scalability and observability of our global data platform. In this role, you are responsible for the operational backbone of our Headless Data Architecture (HDA), ensuring that data and AI pipelines run seamlessly across regions and environments.
Your impact
As a Data Platform Engineer (AI & ML Infrastructure), you play a critical role in enabling our ambition to operate as an AI-powered Workforce-as-a-Service platform. You ensure that the underlying data and AI infrastructure is stable, scalable and ready to support advanced analytics and AI use cases across Europe, the UK, the US and APAC.
You own the day-to-day reliability of the platform — monitoring pipelines, resolving incidents and continuously improving performance and resilience. At the same time, you evolve the platform through automation, infrastructure-as-code and cost optimisation.
You work on a modern data and AI stack built on Databricks and Azure, managing everything from data ingestion pipelines and governance in Unity Catalog to platform-wide observability. You ensure that data flows from raw ingestion to AI-serving layers are robust, traceable and production-ready.
A key part of your role is enabling AI and ML workloads at scale. You support model evaluation frameworks, manage prompt lifecycle and implement guardrails that ensure AI systems are safe, reliable and compliant in production.
You collaborate closely with Data Engineers, AI/ML Engineers and governance stakeholders to ensure the platform is not only performant, but also future-proof, secure and scalable.
What you will do
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Operate and maintain the end-to-end data and AI platform on Databricks and Azure
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Monitor, troubleshoot and resolve production issues across data and ML pipelines
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Manage Unity Catalog governance, access control and data sharing structures
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Build and maintain ingestion and integration pipelines (e.g. via SnapLogic)
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Implement observability frameworks using tools such as OpenTelemetry and Grafana
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Automate infrastructure provisioning using Infrastructure-as-Code (e.g. Terraform)
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Optimise compute usage, scaling policies and overall platform cost efficiency
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Support AI/ML evaluation frameworks and model validation pipelines
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Manage prompt lifecycle, versioning and deployment across environments
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Implement AI guardrails, safety layers and monitoring for production systems
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Contribute to internal tooling and platform acceleration initiatives
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Collaborate across data, platform and AI teams to continuously improve the platform
About the role
You will be part of a growing Data & AI division that is central to the transformation of HeadFirst Group x Impellam into a truly data-driven organisation.
This role sits at the foundation of that ambition — ensuring that everything built on top of the platform, from analytics to AI products, is reliable, secure and scalable.
You work with modern technologies such as Databricks, Azure and advanced observability tooling, while contributing directly to the next generation of AI-enabled platform engineering.
What you bring
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You are a hands-on Data Platform Engineer with a strong focus on reliability, automation and scalability of data and AI infrastructure.
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3–5+ years of experience in platform engineering, DataOps or MLOps
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Strong experience with Databricks (cluster management, jobs, Unity Catalog, Delta Lake)
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Experience with Azure (ADLS, networking, identity, cost management)
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Experience with integration platforms such as SnapLogic or similar iPaaS tools
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Solid experience with Infrastructure-as-Code (Terraform or equivalent)
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Strong knowledge of observability tooling (OpenTelemetry, Grafana or similar)
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Experience with CI/CD pipelines and automated deployments
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Strong Python and/or Scala skills for automation and pipeline scripting
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Understanding of data quality frameworks and monitoring
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Experience with AI/ML platform concepts such as model evaluation, serving or guardrails
What you offer as a professional
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A reliability-first mindset — you prioritise uptime, stability and data quality
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Strong ownership — you take responsibility from incident to resolution
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A collaborative approach across data, platform and AI teams
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A pragmatic mindset balancing performance, cost and scalability
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Clear communication — able to explain platform risks and status to stakeholders
Mobility budget or Lease car: No
Brand: HeadFirst Group
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