dataroots

About the Company

Our Vision:

At Dataroots, we harness the power of AI and data-driven solutions to revolutionize how companies operate. We believe in turning data into a competitive advantage in terms of processes, customer interactions, and legal compliance.

What We Do:

Data Strategy & Governance: Partnering with you for a data-driven future. We focus on enhancing data maturity, driving impactful outcomes, and ensuring compliance.

Artificial Intelligence: Combining domain expertise with advanced AI to optimize operations, mitigate risks, and enrich customer experiences.

Cloud Native Data Platforms: Specializing in robust, scalable cloud-native platforms for an efficient data ecosystem.

Our Culture:

Diversity: Championing diversity for creativity and innovation.

Knowledge Sharing: Promoting growth through open and collaborative learning.

Passion & Pride: Driven by our passion for tech excellence and pride in our work.

Trustworthiness: Building lasting, respectful partnerships.

Global Presence:

As part of the Talan Group, we leverage a global network to deliver top-notch expertise and support. Our presence enables us to provide innovative solutions and managed services worldwide.

Join Us:

We're looking for passionate individuals to join our journey in reshaping the AI and data landscape.

Get in Touch:

Let's connect! We're here for collaborations, questions, or a chat over coffee.

Listed Jobs

Company Name

dataroots

Job Title

IT Recruitment Specialist - Team Lead

Job Description

**Job title** IT Recruitment Specialist – Team Lead **Role Summary** Lead full‑cycle recruitment for IT and business transformation roles while managing and coaching the recruitment team. Own sourcing, interviewing, closing, onboarding, and continuous improvement of recruitment processes for a quality talent pipeline. **Expectations** - 4+ years of hands‑on IT recruitment with proven full‑cycle experience. - Demonstrated leadership in recruiting or team‑lead capacity. - Multi‑language proficiency: Dutch, French, and English. - Strong business acumen, analytical mindset, and data‑driven decision‑making. - Bachelor’s or Master’s degree (any discipline). - Proactive ownership, excellent communication, and collaborative mindset. **Key Responsibilities** - Source, evaluate, interview, close, and onboard candidates for SAP specialists, Business Analysts, Project Managers, and Developers. - Build and maintain a robust network across LinkedIn, events, job fairs, referrals, and creative channels. - Manage job postings, candidate pipelines, and ensure a smooth, engaging candidate experience. - Lead recruitment team: monitor daily activities, track progress, answer queries, and coach staff. - Provide regular updates to HR Manager on metrics, challenges, and insights. - Own and drive improvement projects to streamline processes, enhance data usage, and strengthen external presence. - Monitor recruitment KPIs, analyze performance, and prepare reports for strategic decisions. - Collaborate with hiring managers and stakeholders to understand role requirements and market trends. - Stay current on recruitment best practices, emerging tools, and HR/HRIS trends. **Required Skills** - Expertise in IT talent acquisition and full‑cycle recruiting. - Advanced sourcing techniques (Boolean, X-Ray, niche portals). - Familiarity with ATS platforms and recruitment analytics tools. - Strong stakeholder engagement and negotiation skills. - Leadership, coaching, and team‑motivation abilities. - Excellent written and spoken communication in Dutch, French, and English. - Analytical mindset: ability to interpret data, report insights, and recommend improvements. - Project management and continuous improvement proficiency. - Adaptability to fast‑paced, high‑growth environments. **Required Education & Certifications** - Bachelor’s or Master’s degree (any field). - HR or recruiting certifications (e.g., SHRM‑CP/SHRM‑SHRM, CIPD, or similar) are a plus but not mandatory.

Leuven, Belgium

Hybrid

Senior

01-12-2025

Company Name

dataroots

Job Title

Data & Cloud Engineer

Job Description

**Job title** Data & Cloud Engineer **Role Summary** Senior engineer responsible for architecting, building, and maintaining scalable data pipelines and cloud infrastructure that support AI and machine‑learning initiatives. Leverages DataOps and MLOps practices to ensure high‑quality data flows from ingestion to production, collaborating closely with data scientists, ML engineers, and cloud architects. **Expactations** - Deliver end‑to‑end data platforms that meet performance, reliability, and security requirements. - Lead technical design, review, and mentoring of junior engineering staff. - Maintain clean, maintainable code; enforce coding standards and best practices. - Proactively monitor, troubleshoot, and optimize data pipelines and cloud resources. **Key Responsibilities** - Design and implement ELT pipelines (batch & streaming) using Airflow, Prefect, or Dagster. - Build and deploy data services on platform(s) such as Databricks, Snowflake, Azure Data Services, and/or AWS Data Services. - Provision and manage cloud infrastructure with Terraform; containerize workloads using Docker. - Orchestrate containers in Kubernetes, deploying with Helm charts. - Ensure data quality, lineage, and metadata management across the pipeline. - Integrate Spark for large‑scale data processing where needed. - Collaborate with cross‑disciplinary teams to define data models, schema, and governance policies. - Document architecture, operational procedures, and best‑practice guidelines. **Required Skills** - Strong data engineering fundamentals: relational/NoSQL databases, SQL, Python. - Data pipeline orchestration: Airflow, Prefect, Dagster. - Cloud‑native infrastructure: Terraform, Docker, Kubernetes, Helm. - Platform expertise: Databricks, Snowflake, Azure Data Services, AWS Data Services. - Version control: Git, CI/CD pipelines. - Optional/Plus: Spark, dbt, advanced data modeling, metadata tooling, secure/private networking. **Required Education & Certifications** - Bachelor’s (or Master’s) degree in Computer Science, Software Engineering, Data Engineering, or related field. - Professional certifications in cloud or data platform technologies (e.g., AWS Certified Data Analytics, Azure Data Engineer, Google Professional Data Engineer, Databricks Certified Data Engineer) are highly desirable.

Leuven, Belgium

Hybrid

08-12-2025

Company Name

dataroots

Job Title

Machine Learning Engineer

Job Description

**Job Title** Machine Learning Engineer **Role Summary** Design, develop, and deploy end‑to‑end machine learning and deep‑learning solutions within a DataOps/MLOps framework, collaborating with data engineers, cloud architects, and stakeholders to deliver client‑centric, high‑performance models. **Expectations** - 2+ years working with machine learning and big data. - Master’s or PhD in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics). - Demonstrated passion for advancing AI solutions and continuous learning. - English fluent; Dutch spoken. **Key Responsibilities** - Build, train, and evaluate machine learning and deep‑learning models using production‑ready frameworks. - Implement MLOps pipelines: model versioning, automated testing, CI/CD, monitoring, and rollback mechanisms. - Deploy models to cloud platforms (AWS, Azure, or GCP) and manage associated infrastructure. - Collaborate with data engineers to engineer robust data pipelines and feature stores. - Mentor junior team members and share knowledge across the organization. - Translate complex technical concepts into clear communication for non‑technical stakeholders. **Required Skills** - Proficient in Python (libraries such as scikit‑learn, TensorFlow, PyTorch, or Keras) and SQL. - Experience with ML versioning tools (e.g., MLflow, DVC). - Familiarity with cloud services for ML: compute, storage, and managed ML services. - Understanding of software design principles and type safety. - Strong problem‑solving abilities and pragmatic approach to large‑scale data challenges. - Excellent communication and documentation skills. **Required Education & Certifications** - Master’s or PhD in a quantitative discipline. - Relevant cloud certifications (AWS Certified Machine Learning – Specialty, Azure AI Engineer Associate, or Google Cloud Professional Machine Learning Engineer) are advantageous but not mandatory.

Brussels, Belgium

Hybrid

Junior

12-01-2026

Company Name

dataroots

Job Title

Data platform engineer

Job Description

Job title: Data Platform Engineer Role Summary: Design, build, and maintain scalable, resilient data platforms that enable data engineers, analysts, and scientists to transform raw data into actionable insights efficiently and securely. Own infrastructure, tooling, and standards across cloud, orchestration, governance, and observability to balance performance, cost, and reliability. Expactations: Own the end‑to‑end data platform lifecycle, from cloud provisioning to pipeline execution and monitoring. Collaborate with cross‑functional teams to translate data requirements into platform capabilities. Ensure high availability, data security, compliance, and observability while continuously optimizing for performance and cost. Drive DataOps and MLOps practices to deliver production‑ready solutions. Key Responsibilities: - Design and implement scalable cloud‑based data platforms (AWS, Azure, GCP, or hybrid). - Build and maintain ELT pipelines using Airflow, Prefect, Dagster, Spark, dbt, or equivalent tools. - Provision and manage infrastructure with Terraform, Docker, Kubernetes, and related tooling. - Deploy, configure, and optimize data services such as Databricks, Snowflake, Azure Data Services, or AWS data services. - Implement data governance, security, and compliance controls across the platform. - Establish observability, monitoring, and alerting for data pipelines and infrastructure. - Create and maintain CI/CD pipelines for data and infrastructure code. - Troubleshoot platform issues, perform root‑cause analysis, and implement preventive measures. - Mentor and collaborate with data engineers, scientists, and analysts to promote best practices. Required Skills: - Strong data engineering and cloud architecture expertise. - Proficiency in ELT pipeline tools: Airflow, Prefect, Dagster, Spark, dbt, etc. - Software engineering skills: Git, Python, SQL. - Cloud engineering: Terraform, Docker, Kubernetes, CI/CD. - Experience with at least one major data platform (Databricks, Snowflake, Fabric, Azure Data Services, AWS data services). - Knowledge of data governance, security, and compliance frameworks. - Familiarity with observability tools (monitoring, logging, alerting). - Excellent problem‑solving, communication, and collaboration skills. - Agile mindset and ability to adapt to evolving data needs. Required Education & Certifications: - Bachelor’s or Master’s degree in Computer Science, Data Engineering, Software Engineering, or related field. - Cloud platform certifications (AWS Certified Data Analytics, Azure Data Engineer Associate, GCP Professional Data Engineer) preferred. - Databricks or Snowflake certifications are a plus.

Ghent, Belgium

Hybrid

22-01-2026