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NTT DATA Logo NTT DATA · IT - Software Development

Data & AI Engineer

Belgium, Diegem · Job Posted January 26, 2026
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Job Description

As a Data & AI Engineer at NTT DATA, you will design and implement scalable data solutions on Azure and Databricks. This role requires 3-7 years of experience in data/AI engineering, with a strong focus on Python, PySpark, and SQL. A bachelor's or master's degree in Computer Science or a related field is preferred, along with relevant certifications.

Job Responsibility

  • Build reliable batch/stream pipelines in Databricks (Python/PySpark, SQL) with Delta Lake and Unity Catalog
  • Implement best practices for code quality, testing, documentation, lineage, and cost‑efficient performance
  • Design and deliver GenAI solutions using Azure AI Foundry (projects, prompt flow/evaluation), Azure OpenAI (chat/completions, tool/function calling), and Azure AI Search (indexing, vector search, semantic ranking) with robust RAG patterns
  • Instrument evaluation, grounding, safety checks, and quality metrics for AI features
  • Use MLflow for experiment tracking, model packaging, and deployment
  • standardize environments and feature stores where relevant
  • Build CI/CD for data and AI workloads (e.g., Azure DevOps/GitHub Actions) and implement monitoring & observability (logs, metrics, drift)
  • Provision Azure and Databricks resources with Terraform (modular design, workspaces/state, policies, service principals, Key Vault)
  • Apply RBAC, secrets management, data masking, and governance (Unity Catalog / Purview) with privacy‑by‑design and compliance best practices
  • Partner with product owners, architects, and SMEs to translate use‑cases into simple, secure, cost‑aware solutions
  • Contribute to reference architectures, reusable components, and engineering standards

Requirements

  • 3–7+ years in data/AI engineering (or equivalent impact) delivering production systems on Azure
  • Python (production code, packaging, testing)
  • PySpark
  • SQL
  • Databricks (Repos/Workflows, Delta Lake, Unity Catalog, MLflow)
  • Azure AI Foundry (projects, prompt/eval flows, model endpoints)
  • Azure AI Search (index design, vector embeddings, skillsets/indexers, semantic search)
  • Azure OpenAI (prompt design, grounding, safety filters, function/tool calling, evaluation)
  • Terraform (AzureRM + Databricks providers), modular patterns, pipelines, approvals
  • Git & CI/CD (Azure DevOps or GitHub), code reviews, trunk‑based or GitFlow

Nice to have

  • Azure Data Factory / Fabric pipelines, Synapse, Power BI for hand‑offs to analytics
  • Vector databases (e.g., Azure AI Search vectors, PostgreSQL pgvector), RAG optimization techniques (chunking, retrieval, ranking)
  • Airflow orchestration, Docker/AKS, serverless (Azure Functions), FastAPI for serving
  • Data governance (Microsoft Purview), cost management, FinOps practices
  • Domain exposure to regulated environments and GDPR data protection
  • BSc/MSc in Computer Science, Data/AI, or similar (or equivalent experience)
  • Microsoft: Azure Data Engineer Associate, Azure AI Engineer Associate
  • Databricks: Lakehouse Fundamentals / Data Engineer / Machine Learning certifications
  • HashiCorp: Terraform Associate
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