Data Engineer - Microsoft Fabric & PySpark

NTT DATA Global Delivery Services Ltd; Bengaluru; Remote; INR 10,649,000 - 15,489,000; Full time

Job summary

NTT DATA Global Delivery Services Ltd seeks a Fabric Data Engineer skilled in PySpark to design and optimize enterprise data pipelines on Azure and Fabric platforms. The role focuses on building scalable data workloads, integrating diverse data sources, and supporting modernization efforts across cloud data architectures.

The candidate will collaborate with data architects, Power BI developers, analysts, and engineers to deliver secure and high‑performing data solutions using Azure Synapse

Qualifications

• Strong hands-on experience with Microsoft Azure data services, Azure Synapse Analytics and/or Microsoft Fabric.
• Experience designing, developing, implementing, and optimizing scalable data pipelines and data platforms using Azure-based tools.
• Proficiency in Python, PySpark, Spark SQL and developing data transformations.
• Familiarity with data lakes, data warehouses, lakehouse architectures and data integration patterns.

Responsibilities

• Design, develop, and maintain enterprise data solutions using Microsoft Azure.
• Build scalable data ingestion, transformation, and processing solutions.
• Develop and optimize data pipelines with Azure Data Factory, Azure Synapse Analytics, and/or Microsoft Fabric.
• Create data models and orchestration workflows across Azure services.
• Develop notebooks using Python, PySpark, and Spark SQL.
• Support migration and modernization of legacy data platforms to Azure.

Skills

Azure data services

Azure Synapse Analytics

Microsoft Fabric

Python

PySpark

Spark SQL

Data engineering

ETL/ELT

Tools

Azure Data Factory

Fabric Data Factory

Azure Data Lake Storage Gen2

Delta Lake

OneLake

Job description

Fabric Data Engineer - Pyspark Req ID: 390147 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. We are currently seeking a Fabric Data Engineer - Pyspark to join our team in Bangalore, Karnātaka (IN-KA), India (IN). Microsoft Fabric Data Engineer India Migrate Pipeline migration using pyspark/sql Microsoft Azure Data Engineer to join our growing Data & Analytics organization in the United States. The ideal candidate will have strong hands‑on experience with Microsoft Azure data services, Azure Synapse Analytics and/or Microsoft Fabric, data engineering, data integration, data transformation, and enterprise data platforms. The Microsoft Azure Data Engineer will be responsible for designing, developing, implementing, and optimizing scalable data pipelines, data warehouses, Lakehouses, and enterprise data solutions using the Microsoft Azure data ecosystem. Candidates should have significant experience working with Azure Synapse Analytics or Microsoft Fabric, with experience across both platforms considered highly desirable. This role will work closely with data architects, Power BI developers, analysts, software engineers, DevOps engineers, and business stakeholders to build reliable, scalable, secure, and high‑performing enterprise data platforms.

Key Responsibilities

Azure Data Engineering

• Design, develop, and maintain enterprise data solutions using Microsoft Azure.
• Build scalable data ingestion, transformation, and processing solutions.
• Develop and optimize data pipelines using Azure Data Factory, Azure Synapse Analytics, and/or Microsoft Fabric.
• Design solutions that integrate data from databases, APIs, files, SaaS platforms, cloud applications, and enterprise systems.
• Develop reusable data engineering frameworks and components.
• Implement batch and near-real-time data processing solutions.
• Monitor, troubleshoot, and optimize Azure data workloads.
• Support modernization and migration of legacy data platforms to Azure.

Azure Synapse Analytics & Microsoft Fabric

• Design and develop data solutions using Azure Synapse Analytics and/or Microsoft Fabric.
• Build enterprise data warehouses and Lakehouse solutions.
• Develop data pipelines and orchestration workflows.
• Work with Synapse Pipelines, Fabric Data Factory, and Azure Data Factory.
• Develop notebooks using Python, PySpark, and Spark SQL.
• Build and optimize data transformation processes.
• Work with Synapse SQL, Fabric Data Warehouse, Fabric Lakehouse, and related technologies.
• Support migration and modernization initiatives between traditional Azure architectures, Azure Synapse, and Microsoft Fabric.
• Evaluate appropriate technologies based on performance, scalability, cost, security, and business requirements.

ETL/ELT & Data Integration

• Design and develop robust ETL and ELT pipelines.
• Ingest structured, semi-structured, and unstructured data from multiple enterprise sources.
• Integrate data from databases, APIs, files, SaaS applications, and cloud platforms.
• Develop reusable ingestion and transformation frameworks.
• Implement incremental data loads and Change Data Capture (CDC) strategies.
• Develop data validation, reconciliation, and error-handling processes.
• Troubleshoot pipeline failures and data integration issues.
• Optimize pipelines for performance, scalability, reliability, and cost.

Data Lake, Lakehouse & Data Warehouse

• Design and implement modern Data Lake, Lakehouse, and Data Warehouse architectures.
• Work with Azure Data Lake Storage Gen2 and Microsoft OneLake.
• Implement Bronze, Silver, and Gold data layers.
• Design dimensional data models using Star and Snowflake schemas.
• Develop fact and dimension tables.
• Implement Slowly Changing Dimensions (SCD).
• Work with Delta Lake and related technologies.
• Implement partitioning and performance optimization strategies.
• Support enterprise data warehouse modernization and migration initiatives.

Azure Data Platform

• Work with Microsoft Azure technologies including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure SQL Database, Azure SQL Managed Instance, Azure Functions, Azure Key Vault, Azure Event Hubs, Azure Storage, Microsoft Entra ID, Microsoft Fabric.
• Additional responsibilities include developing integrations between Azure services and enterprise applications.
• Implement secure and scalable cloud data architectures.
• Support cloud migration and modernization initiatives.
• Monitor Azure resources and optimize platform performance and cost.
• Apply cloud architecture and engineering best practices across data solutions.

Microsoft Fabric

• Develop solutions using Fabric Lakehouse and Data Warehouse.
• Build pipelines using Fabric Data Factory.
• Develop Dataflows Gen2.
• Work with OneLake.
• Develop Fabric Notebooks using PySpark, Python, and Spark SQL.
• Implement Delta Lake-based data architectures.
• Support Direct Lake and Power BI integration.
• Manage Fabric workspaces and deployment processes.
• Monitor and optimize Fabric capacity utilization.

Python, PySpark & Data Processing

• Develop scalable data transformations using Python, PySpark, and Spark SQL.
• Process large datasets using distributed computing.

Work Location: United States (Remote - ATL hybrid is a plus).

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 is an equal opportunity employer.

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