Website Microsoft

Consultant – Data Engineer + AI (Microsoft GCID, Bangalore)

Opportunity Overview

Attribute Details
Organization Microsoft Industry Solutions – Global Center for Innovation and Delivery (GCID)
Job ID & Posted Date Job ID: 200045809
Role Title Consultant – Data Engineer + AI
Location & Work Site Bangalore, Karnataka, India
Travel Commitment Less than 25%
Profession & Discipline Consulting Services / Technology Consulting (Individual Contributor)
Employment Type Full-Time
Required Experience 4 – 6 years in Data Engineering, AI Pipelines, and Cloud Consulting

Role Scope & Technical Architecture

The Data Engineer + AI Consultant delivers end-to-end cloud modernisation, enterprise data pipelines, and Generative AI solutions for global Microsoft clients, operating within GCID’s 2000+ delivery organisation:

[Legacy Data Ingestion] ➔ [ETL / ELT Pipelines (ADF/Fabric)] ➔ [Feature Engineering & Vector Search] ➔ [GenAI / RAG Deployment (Azure OpenAI)]

Core Responsibilities

  • Data Platform Modernisation: Design and deploy modern data platform architectures utilising Microsoft Fabric, Azure Synapse Analytics, Azure Data Factory (ADF), and Azure Databricks.

  • AI & GenAI Pipeline Integration: Build AI-ready data pipelines, feature stores, and RAG (Retrieval-Augmented Generation) architectures integrating Azure AI Search, Azure OpenAI, and Azure Foundry.

  • Risk & Escalation Management: Define technical dependencies, manage delivery risks, design contingency frameworks, and execute technical escalations for strategic engagements.

  • Consulting & Co-Creation: Partner with client stakeholders, system architects, and account teams to translate business challenges into technical solutions, driving Azure consumption.

  • DataOps & MLOps Execution: Implement automated CI/CD deployment pipelines, automated testing, continuous integration, and Responsible AI principles using Azure DevOps.

Candidate Qualifications & Technical Skills Matrix

Minimum Qualifications

  • Experience: 4 to 6 years of hands-on data engineering, cloud analytics, and IT consulting delivery.

  • Education: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.

  • Programming Core: Advanced programming skills in Python and SQL.

Technical & Platform Skills Matrix

Skill Domain Technical Stack & Core Competencies
Data Engineering & Fabrics

• Core Services: Microsoft Fabric, Azure Synapse Analytics, Azure Databricks, Spark


• ETL/ELT: Azure Data Factory (ADF), SSIS, Airflow, Informatica, Talend
AI, GenAI & MLOps

• AI Stack: Azure OpenAI, Azure AI Search, Azure AI Foundry, Document Intelligence


• Frameworks: RAG, LangChain, LangGraph, Vector Indexing, Prompt Engineering


• MLOps: Feature engineering, PyTorch/TensorFlow exposure, Azure Machine Learning
Data Architecture & DevOps

• Dimensional modeling, Lambda/Kappa architectures, DataOps via Azure DevOps


• Multitenant security, access control, and Responsible AI governance
Preferred Certifications

• DP-600 (Fabric Analytics Engineer Associate)


• AI-102 (Azure AI Engineer Associate)


• AZ-305 (Azure Solutions Architect Expert)

Selection Workflow & Evaluation Pipeline

[Application Screening] ➔ [Technical Recruiter Assessment] ➔ [Data & AI Technical Interview Loop] ➔ [Consulting & Scenario Presentation]

  1. Resume Review: Verification of 4–6 years in Data Engineering, Python proficiency, Azure Data platform depth, and client consulting history.

  2. Technical Deep Dive: Technical evaluation covering SQL/Python coding, ETL/ELT pipeline design in ADF/Fabric, Spark performance tuning, and MLOps/RAG architecture concepts.

  3. Consulting & System Design Round: Scenario-based interview evaluating client communication, risk mitigation, trade-off analysis, and Azure OpenAI architecture design.

  4. Final Hiring Manager Loop: Assessment of cultural fit, continuous learning orientation, hybrid office commitment (Bangalore), and less than 25% travel readiness.

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