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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 insurance sector, is looking for an AI Governance Officer to operationalize an effective and compliant framework. The role acts as the primary liaison between business units and risk management functions to ensure alignment with both regulatory requirements and business objectives.
Our client, a major player in the financial services sector, is undergoing a digital and data-driven transformation. The project involves building and scaling a modern, cloud-native data platform to deliver robust analytics and reporting solutions across the organization.
Our client, a leading organization in the financial sector, is looking for a professional to join their BI team. This role focuses on maintaining and optimizing reporting solutions while supporting the transition to a modern cloud-based data platform.
Our client, a major player in the maritime and logistics sector, is seeking a Data Governance Analyst to support their data and analytics department. This role focuses on unlocking data sources to drive data-driven insights and supporting the governance team across a variety of strategic projects.
Our client, a leading organization in the maritime sector, is focused on transforming environmental data into actionable insights to support strategic water management initiatives. The project involves interpreting, defining, and preparing complex datasets for advanced reporting and machine learning applications within a dedicated data governance team.
Our client, a leading organization in the transport and logistics sector, is looking for a Data & Platform Engineer to help build and scale their next-generation data science and AI platform. This role focuses on designing and maintaining the data foundations and infrastructure that power analytics, machine learning, and AI solutions across the organization.
Our client, a prominent public sector organization, is seeking two specialists to support the migration of their data warehouse to the Microsoft Azure cloud. This project focuses on modernizing reporting capabilities through the implementation of Microsoft Fabric and Power BI. The role involves translating business processes into technical data models to ensure high-performance data delivery.
Our client, a leading organization in the environmental utility sector, is looking for a specialist to build scalable, high-quality data products. The project involves modernizing digital infrastructure to enhance water management through advanced data modeling and cloud-driven engineering.
Onze klant, een toonaangevende en mensgerichte organisatie gespecialiseerd in dienstverlening voor ondernemers, zoekt een Corporate Data Analist om complexe data te vertalen naar strategische groei. In deze rol combineer je technische expertise met business-inzicht om de digitale maturiteit en operationele efficiëntie van de organisatie direct te beïnvloeden.
Our client, a leading public administration organization, is undertaking a major digital transformation to modernize its core legacy systems into a microservices-based architecture. The project focuses on building a flexible and scalable digital platform using an API-first and event-driven approach on Kubernetes.
Our client is looking for an autonomous professional to strengthen their data platform capabilities. The project involves maintaining a modern infrastructure, managing cloud environments, and optimizing high-velocity data ingestion pipelines within a distributed architecture.
Onze klant, een vooraanstaande en mensgerichte organisatie, is op zoek naar een Data Analist om complexe gegevens om te zetten in strategische inzichten. In deze rol krijg je de kans om een cruciale bijdrage te leveren aan de segmentstrategieën en de dienstverlening continu te verbeteren door middel van geavanceerde analyses.
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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