Data Engineer (AWS, Azure & Microsoft Copilot Studio)

Req ID: 384613

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.

We are currently seeking a Data Engineer (AWS, Azure & Microsoft Copilot Studio) to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

Job Description – Data Engineer (AWS, Azure & Microsoft Copilot Studio)

Job Title: Data Engineer – AWS, Azure & Microsoft Copilot Studio
Location: India, Remote
Experience: 5+ Years
Domain Preference: Healthcare, Life Sciences, MedTech, or Pharmaceutical

Position Overview

We are seeking a highly motivated and experienced Data Engineer to design, develop, and maintain modern cloud-based data platforms while enabling next-generation artificial intelligence and Microsoft Copilot solutions.

The ideal candidate will have strong hands-on expertise in the AWS data ecosystem , working knowledge of Azure data technologies , and experience developing AI-powered solutions using Microsoft Copilot Studio, Power Platform, Generative AI, and Large Language Models .

The role will be responsible for building scalable data ingestion and transformation pipelines, developing enterprise data models, implementing data governance controls, and integrating enterprise data assets with AI agents, automation workflows, knowledge search solutions, and Generative AI applications.

Key Responsibilities

Data Engineering

• Design, develop, and maintain scalable ETL and ELT data pipelines.

• Build reusable data ingestion frameworks for APIs, relational databases, SaaS platforms, files, enterprise applications, and streaming data sources.

• Develop and optimize data models supporting analytics, reporting, business intelligence, AI, and machine learning workloads.

• Implement data quality checks, reconciliation processes, metadata management, data lineage, and governance controls.

• Support enterprise data lake, lakehouse, and cloud data warehouse initiatives.

• Design efficient batch and real-time data-processing solutions.

• Troubleshoot data-pipeline failures, performance issues, and data-quality defects.

• Collaborate with data architects, analysts, AI engineers, application teams, and business stakeholders to deliver scalable data solutions.

AWS Data Engineering

• Design and develop data solutions using:

  • AWS Glue

  • Amazon S3

  • Amazon Athena

  • Amazon Redshift

  • AWS Lambda

  • Amazon EventBridge

  • AWS Identity and Access Management

  • Amazon Bedrock, preferably

• Build serverless and event-driven data-processing solutions.

• Develop data integration workflows between AWS services and enterprise applications.

• Configure appropriate security, access controls, encryption, and monitoring.

• Optimize AWS infrastructure for performance, reliability, scalability, and cost efficiency.

• Support data orchestration, scheduling, logging, alerting, and operational monitoring.

Azure Data Engineering

• Develop and maintain data solutions using:

  • Azure Data Factory

  • Azure Synapse Analytics

  • Azure Databricks

  • Azure SQL Database

  • Azure Data Lake Storage Gen2

  • Microsoft Fabric

  • Azure OpenAI

  • Azure Functions

• Build and manage Azure-based data pipelines and integration workflows.

• Support enterprise analytics, reporting, AI, and machine learning workloads.

• Develop scalable data-processing solutions using PySpark, Spark SQL, and Databricks.

• Integrate Azure data services with Microsoft Power Platform and AI solutions.

• Implement appropriate security, monitoring, and operational controls across Azure environments.

Microsoft Copilot Studio and Generative AI Integration

• Design and develop enterprise AI agents using Microsoft Copilot Studio.

• Integrate Copilot Studio solutions with:

  • Microsoft Dataverse

  • SharePoint

  • Microsoft Graph

  • Power Automate

  • Microsoft Teams

  • REST APIs

  • Enterprise data platforms

• Build knowledge-grounded Copilot experiences using structured and unstructured enterprise data.

• Develop enterprise search and retrieval solutions for AI assistants and Copilot applications.

• Implement Retrieval-Augmented Generation architectures for secure and context-aware AI responses.

• Create workflow automation solutions using Power Automate and Power Platform.

• Integrate Large Language Models with enterprise applications, APIs, databases, and cloud data platforms.

• Develop and optimize prompts, grounding strategies, conversation flows, topics, actions, and connectors.

• Support agentic AI, AI-assisted automation, and multi-step workflow orchestration initiatives.

• Implement appropriate security, access control, monitoring, and responsible AI practices for enterprise AI solutions.

DevOps, Infrastructure and Automation

• Implement CI/CD pipelines for data engineering and AI solutions.

• Automate build, testing, deployment, and release processes using Azure DevOps and GitHub Actions.

• Support Infrastructure as Code using Terraform or Bicep.

• Manage code repositories, branching strategies, environment configurations, and release processes.

• Implement automated testing for data pipelines, APIs, and integration workflows.

• Monitor application, pipeline, and infrastructure health, performance, failures, and operational metrics.

• Support development, testing, staging, and production environments.

Required Qualifications

Experience

• Minimum 5+ years of overall experience in data engineering, cloud engineering, analytics engineering, or a related technology role.

• Minimum 3+ years of hands-on experience working with AWS data technologies.

• Minimum 1+ year of experience working with Azure data technologies.

• At least 1+ year of experience working with Generative AI, Large Language Models, Microsoft Copilot Studio, or AI-powered enterprise applications.

• Experience designing and developing production-grade ETL and ELT pipelines.

• Experience working in Agile or Scrum-based product delivery teams.

• Experience integrating cloud data platforms with APIs, databases, SaaS applications, and enterprise systems.

Programming and Data Engineering Skills

• Strong programming experience with Python.

• Advanced SQL development and query-optimization skills.

• Hands-on experience with PySpark and Spark SQL.

• Strong understanding of data modeling, data warehousing, lakehouse, and data lake concepts.

• Knowledge of batch processing, event-driven architectures, and streaming data patterns.

• Experience implementing data-quality, lineage, governance, and monitoring controls.

AWS Skills

• AWS Glue

• Amazon S3

• Amazon Athena

• Amazon Redshift

• AWS Lambda

• Amazon EventBridge

• AWS IAM

• Amazon Bedrock, preferred

Azure Skills

• Azure Data Factory

• Azure Synapse Analytics

• Azure Databricks

• Azure Data Lake Storage Gen2

• Azure SQL

• Microsoft Fabric

• Azure OpenAI

• Azure Functions

AI and Microsoft Copilot Skills

• Microsoft Copilot Studio

• Microsoft Power Platform

• Power Automate

• Microsoft Dataverse

• Prompt engineering

• Retrieval-Augmented Generation

• Large Language Model integration

• Enterprise knowledge grounding

• REST API integration

• AI agent and workflow development

Database Skills

• SQL Server

• PostgreSQL

• Snowflake, preferred

• Azure Cosmos DB, preferred

DevOps and Automation Skills

• Azure DevOps

• GitHub Actions

• Git and source-code management

• Terraform or Bicep

• CI/CD implementation

• Monitoring, logging, and deployment automation

Preferred Qualifications

• Experience in the Healthcare, Life Sciences, MedTech, Biotechnology, or Pharmaceutical industry.

• Understanding of regulated-data environments, data privacy, security, and governance requirements.

• Experience integrating enterprise applications such as SAP, Salesforce, ServiceNow, or similar platforms.

• Experience building enterprise AI assistants, conversational agents, or intelligent automation solutions.

• Exposure to Microsoft Fabric and Azure AI Foundry.

• Experience building enterprise knowledge search, semantic search, or document-retrieval solutions.

• Experience working with vector databases, embeddings, and retrieval frameworks.

• Familiarity with Generative AI governance, model evaluation, responsible AI, and security practices.

• Knowledge of cloud cost optimization and FinOps principles.

• Relevant AWS, Microsoft Azure, Data Engineering, Power Platform, or AI certifications.

Key Competencies

• Strong analytical and problem-solving abilities.

• Ability to design scalable, secure, and maintainable enterprise solutions.

• Strong communication and stakeholder-management skills.

• Ability to work effectively across data, application, infrastructure, security, and business teams.

• Ability to translate business requirements into technical data and AI solutions.

• Strong ownership, accountability, and attention to detail.

• Ability to work independently and manage multiple priorities in a fast-paced delivery environment.

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, 

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