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NTT DATA Services

Data Engineer Advisor

NTT DATA Services Bangalore, Karnataka, India

IT Services and IT Consulting · 10,001+ employees

20 h ago
data-engineer Principal (10+ yrs) Full-time India
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About the role

Design and build scalable Azure data pipelines and modern Lakehouse architectures using Microsoft Fabric and Synapse. Collaborate with stakeholders to deliver high-performance data solutions that support AI use cases like RAG and vector search.

What they look for

Azure Data Factory Azure Synapse Microsoft Fabric Azure Data Lake Storage Cosmos DB Python SQL NoSQL Data Engineering AI Pipelines RAG Vector Search CI/CD Azure DevOps Data Modeling Data Quality

Requirements

Requires over 10 years of total experience with at least 6 years of relevant Azure data engineering expertise. Candidates must possess strong Python and SQL skills along with hands-on experience in Azure data ecosystems.

Full description

**Candidate required only from Bengaluru or Gurgaon location

Key responsibilities

  • Design and build scalable Azure data pipelines using ADF, Synapse and Microsoft Fabric
  • Develop modern Lakehouse architectures and AI-ready data platforms
  • Engineer solutions for structured, semi-structured and unstructured data
  • Work with Azure Data Lake, Cosmos DB and Azure SQL/Synapse
  • Support AI use cases including RAG, vector search and Azure AI Search
  • Collaborate with business stakeholders to translate requirements into data solutions
  • Deliver production-ready, high-performance data engineering solutions

Key experience required

  • 10 years total & 6+ years relevant experience
  • Strong experience as an Azure Data Engineer
  • Hands-on expertise with ADF, Synapse, Microsoft Fabric and ADLS Gen2
  • Experience with Azure Cosmos DB and NoSQL data modelling
  • Exposure to AI/GenAI data pipelines, including RAG, embeddings or vector search
  • Strong Python and SQL development skills
  • Experience with data discovery, profiling and data quality frameworks
  • Knowledge of CI/CD and Azure DevOps practices

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