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Find your next Data & AI role and turn complex data into insights, intelligent systems, and scalable solutions that drive smarter decisions across analytics, platforms, and AI-powered products.
Our client, a leading organization in the transport sector, is looking for a specialist to manage the operational phase of its AI-driven services. This role focuses on maintaining the reliability, performance, and security of production-scale AI agents and retrieval-based systems.
Our client, a prominent organization in the public sector, is looking for a BI Data Engineer to join their Business Intelligence team. This role involves designing, developing, and maintaining a high-performance data platform to support reporting and data-driven decision-making across the organization.
Our client, a leading organization in the transportation and infrastructure sector, is looking for a specialist to manage and secure their SAS platform. This role involves administering a Linux-based environment, developing ETL programs, and supporting analytical tools like R and Python. The position combines platform stability management with active development in a large-scale data warehouse.
Our client, a leading organization in the utility and infrastructure sector, is seeking an analytical professional to support their asset planning department. The role focuses on digitalizing budgeting processes and integrating legacy data into a centralized data platform to enhance long-term investment planning.
Our client, a leading organization in the utility sector, is looking for an expert to drive the digitalization of their asset budgeting and planning processes. This role focuses on transitioning complex financial models into a centralized data architecture to support long-term technical investment strategies.
Our client, a leading organization in the telecommunications sector, is looking for a specialist to oversee address data and geospatial systems for large-scale infrastructure projects. This role focuses on ensuring data integrity across network deployment phases, automating reporting cycles, and developing scripts to optimize design engineering workflows.
Our client, a leading organization in the energy sector, is looking for a professional to drive its data-centric strategy. The role focuses on closing the gap between business and data by designing solid foundations for metadata, responsibilities, and discoverability to leverage a corporate data platform.
Our client, a leading organization in the transportation sector, is seeking an expert to drive their Data Retention Initiative as part of a broader enterprise data strategy. The project aims to operationalize data retention policies by defining and implementing end-to-end lifecycle management plans across various business units and information domains.
Our client, a leading organization in the public health sector, is looking for a Senior Data Governance Expert to join their data office and drive transformation. This role focuses on implementing and coordinating data governance frameworks, coaching data stewards, and leading data quality initiatives to support strategic public policies.
Our client, a prominent organization in the public sector, is seeking an AI Engineer to develop and manage technical components that enable AI integration. The role focuses on building agents, retrieval solutions, and MLOps pipelines while supporting teams in implementing AI across various use cases.
Our client, a prominent organization in the public sector, is looking for an Expert AI Architect to define and monitor the target architecture for artificial intelligence. The project focuses on ensuring models, agents, and data flows align coherently with the broader architecture while meeting security and privacy requirements.
Onze klant, een toonaangevende en mensgerichte organisatie, zoekt een Lead Data Analist die analytische expertise combineert met een strategische visie. In deze rol bouw je mee aan hoogwaardige analytics-oplossingen en bepaal je de standaarden die de organisatie naar een hoger niveau tillen. Je krijgt de kans om impact te maken binnen een professionele omgeving waar innovatie en persoonlijke groei centraal staan.
Own data and AI initiatives end to end, from raw data to decision-making tools and production-ready models.
Data Analyst
Turn chaotic data into clear insights, build dashboards people actually use, answer “can you pull this real quick?” requests that never take five minutes, and help teams make decisions backed by numbers not gut feelings.
Data Scientist
Build predictive and statistical models, uncover patterns humans miss, communicate complex concepts simply, and spend most of your time preparing messy data so your models can shine during that final demo.
Data Architect
Design modern data ecosystems such as lakes, warehouses, streams and icebergs that scale, ensure data flows cleanly from source to insight, and prevent the entire organization from drifting into a spaghetti mess of pipelines and shadow databases.
Data Engineer / ETL Engineer / DWH Engineer
Build and maintain reliable data pipelines, transform raw data into trusted datasets, design performant warehouses, and ensure downstream teams aren’t trying to make decisions using incomplete or inconsistent data.
Analytics Engineer
Live between data engineering and analytics, own the transformation layer, write maintainable dbt models, and turn raw tables into clean, documented, analyst-ready datasets that don’t break every other day.
BI Analyst
Turn data into business intelligence, build dashboards and visualizations that drive decisions, and explain why numbers differ between systems without blaming “the data” unless it really is the data.
BI Developer
Build enterprise BI solutions, design semantic layers and optimized data models, and create dashboards fast enough that executives stop emailing you Excel screenshots asking for “the latest version.”
AI Engineer
Build and deploy AI solutions, integrate ML models into production systems, and bridge the gap between experimental notebooks and real-world applications that scale reliably and deliver measurable business value.
Machine Learning Engineer
Take ML models from prototype to production, build training and inference pipelines, monitor performance in the wild, and make sure the model that worked on test data doesn’t collapse under real user behavior.
MLOps Engineer
Automate the end-to-end ML lifecycle, manage feature stores, versioning, and model monitoring, detect drift before it becomes a crisis, and make deploying ML models as stable as deploying regular software.
AI Architect
Design enterprise-level AI architectures and strategies, evaluate where AI adds real value, define data/model pipelines, and ensure solutions integrate cleanly instead of becoming unmaintainable collections of experiments.
Prompt Engineer / LLM Engineer
Optimize prompts and model interactions, build evaluation frameworks for LLM performance, fine-tune models for specific use cases, and navigate the constantly evolving world of generative AI where best practices change monthly.
Data Product Manager
Define the roadmap for data products and platforms, translate business needs into data requirements, and balance the tension between delivering quick insights and building scalable foundations for long-term analytics.
Power BI Developer
Build interactive Power BI dashboards, optimize DAX that tests your patience (and CPU), improve report performance, and create visuals that make insights obvious—even for non-technical audiences.
Power BI Analyst
Translate business questions into Power BI reports, connect to every data source imaginable, build DAX measures that reflect business logic, and explain discrepancies between Power BI reports and old Excel files.
Microsoft Fabric Engineer
Build solutions across the Fabric ecosystem, manage lakehouses and pipelines, and orchestrate end-to-end analytics flows in Microsoft’s unified data platform.
Microsoft Fabric Architect
Design enterprise data architectures on Fabric, plan migrations from legacy systems, and architect solutions that use Fabric’s capabilities effectively without locking the organization into long-term complexity.
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