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Agilytic

Data science consulting and analytics services

Senior Data Platform Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeBrussels, Belgium

About the Job

Requirements

  • A master's degree in engineering, computer science, mathematics, statistics, or a related quantitative discipline.
  • At least 5 years of professional experience in data engineering or platform engineering.
  • Experience designing and operating production data platforms on at least one major cloud: AWS, Azure, or Google Cloud Platform.
  • Hands-on experience with a modern data stack such as Databricks, Snowflake, Microsoft Fabric, dbt, and Airflow or equivalent, plus solid SQL and Python.
  • Experience building or operating components of an AI or machine learning platform, including model deployment, inference infrastructure, retrieval-augmented generation pipelines, vector databases, and evaluation and observability of large language model applications.
  • Experience with continuous integration and continuous delivery, infrastructure as code such as Terraform or equivalent, and DevOps practices applied to data.
  • Experience with data modeling and analytics engineering patterns, including medallion, dimensional, and contract-driven pipelines.
  • Knowledge of security and governance basics, including identity and access management, secrets management, lineage, data quality, and GDPR-aware design.
  • Experience working directly with client stakeholders in a consulting or in-house lead role.
  • Fluency in English and fluency in French or Dutch.
  • A valid type B driving license (Belgian car license) or equivalent.
  • Eligibility to work in Belgium and the European Union.
  • Strong technical judgment in selecting proven or newer tools appropriately.
  • Pragmatism in delivering working platforms.
  • Curiosity about AI, including having built, evaluated, and debugged large language model systems in real settings.
  • A coaching mindset and interest in improving other engineers' skills.
  • Clear written and spoken communication with technical and non-technical audiences.

Responsibilities

  • Own the architecture of client data and AI platforms, including ingestion, storage, transformation, orchestration, serving, observability, and security.
  • Set up and harden production environments on modern cloud stacks and with data-platform tooling.
  • Design and implement the AI Platform layer, including model serving, feature stores, retrieval-augmented generation pipelines, vector stores, evaluation and monitoring, cost and latency controls, and guardrails for large language model applications.
  • Provide senior technical support across active engagements through code reviews, troubleshooting difficult problems, performance tuning, and unblocking junior and mid-level engineers.
  • Coach the team through pairing, technical write-ups, internal sessions, and clear standards.
  • Engage directly with client technology leads, architects, and chief technology officers, translating business intent into defensible technical designs.
  • Contribute to proposals and scoping discussions when senior technical credibility is needed.
  • Help shape the company's point of view on data and AI platforms and feed it back into its offerings.

Desired Qualifications

  • Seven to eight years of professional experience is the ideal profile.
  • Strong proficiency in Dutch is particularly valued.

About the Company

Agilytic

Data science consulting and analytics services

Agilytic is a data science and engineering consultancy that helps organizations turn data into strategic decisions through project-based engagements. It designs multi-year roadmaps, 8–12 week proofs of value, and large deployments, offering data science, data engineering, data visualization, automation, and AI implementation, with domain work in telecom, real estate, retail, and healthcare (including GIS for real estate and RFM models for retail). Unlike some firms, Agilytic blends telecoms-rooted experience with cross-industry expertise, leverages certified professionals, and emphasizes data storytelling to translate complex data into actionable insights. Its goal is to deliver measurable outcomes and ROI by building practical data capabilities and executing well-scoped, repeatable projects.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Waterloo, Belgium
Founded
2015

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