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Technical BA
IQ Staffing B.V.
About the role
Technical Business Analyst — Enterprise AI & MLOps Platform
A business analyst role for someone who is genuinely technical. You sit between the data scientists and AI teams who want to get models into production and the engineers building the platform that lets them — turning "we need this" into requirements, processes and a backlog that a team can actually work from.
Two things make it more than a translation job. You're responsible for pushing the platform's security, risk and compliance controls forward, in an environment where model workloads touch sensitive data. And you're partly selling it: the platform only matters if teams onboard onto it, so promoting it and guiding new users through onboarding is part of the work.
The environment
Our client is a large financial organisation, and the platform in question is where its machine learning, AI and agentic workloads go to run in production — batch and real-time model serving, model management, secure storage and integration with data sources, all on Azure.
Its users are hundreds of data scientists, model developers and AI teams across the organisation, with thousands more who could be. You'd work as part of one technical team alongside engineers, the product owner, business stakeholders and senior management.
What you'll do
Get to the question behind the request, and turn it into technical requirements, processes and concrete action plans.
Strengthen the platform's security, risk and compliance position through better controls, governance, documentation and process.
Support the product owner on vision, roadmap, daily priorities and a backlog that stays manageable.
Promote the platform internally and convince new teams to onboard.
Guide new users through onboarding so their first experience is a smooth one.
Explore emerging technology — agentic AI, Azure AI Foundry — together with engineers and business stakeholders.
Technical ground
Core: Azure infrastructure (resources, pipelines, repositories, subscriptions) · Databricks · model serving · model governance · data & AI concepts
Also in the mix: orchestration tooling · data storage practices · agentic AI · Azure AI Foundry · Scrum and DevOps ways of working
What you'll bring
Must-haves
A good working understanding of data, analytics and AI concepts — enough to hold your own with engineers and data scientists.
Intermediate Azure infrastructure knowledge: how resources, pipelines, repositories and subscriptions fit together.
Familiarity with Databricks, orchestration tools, model development, model governance and data storage practices.
Experience in a Scrum-based DevOps team, supporting backlog prioritisation and roadmap development.
Comfort working with security, risk and compliance requirements rather than around them.
Strong communication, stakeholder management and information-analysis skills.
Nice to have
Exposure to agentic AI and Azure AI Foundry.
A background in financial services or another regulated environment.
You're curious and proactive, and you're willing to push back on a request when the question behind it doesn't hold up. In this role that's the difference between a backlog and a wish list.
Good to know
36 hours per week.
A pre-employment screening is part of the process — standard for the financial sector.
You'll need a valid EU work permit or existing right to work in the Netherlands.