Lead Data Engineer - Data Engineering 4C

Lead Data Engineer Ready to turn bold ideas into real-world impact?  At Genpact, we don’t just adapt to change, we lead it. AI and digital innovation are transforming the way businesses work, and we’re at the forefront of it. Genpact’s AI Gigafactory , our industry-first accelerator, exemplifies how we scale advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. Whether tackling complex challenges through large-scale models or agentic AI , our breakthrough solutions tackle companies’ most complex challenges.   If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment.    Genpact (NYSE: G) is an agentic and advanced technology solutions company. We leverage process intelligence and artificial intelligence to deliver measurable outcomes. With a strong partner ecosystem and decades of client trust, we provide innovative solutions that transform how businesses run. Powered by a team with an active learning mindset and client centricity at its core, we deliver lasting value for the world’s leading enterprises.  Get to know us at genpact.com and on LinkedIn , YouTube , X , and Facebook .

Senior Data Engineer As a Senior Data Engineer within our Enterprise Data and Analytics team, you’ll be at the forefront of a company-wide digital transformation. We’re looking for a forward-thinking engineer who brings deep technical expertise and a passion for building scalable, AI-ready data platforms. In this role, you’ll architect and implement modern data solutions that power intelligent applications, streamline operations, and deliver measurable business value. You’ll work closely with cross-functional teams to design robust pipelines, integrate diverse data sources, and enable advanced analytics and generative AI capabilities.   Key Responsibilities: * Design, develop, and maintain scalable data pipelines and ETL processes using Azure Data Factory, Azure Data Bricks, and other Azure services. * Implement and optimize data storage solutions using Azure Data Lake, Azure SQL Database, and Delta Lake to support analytics and reporting needs. * Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality, reliable datasets. * Ensure data security, compliance, and governance by applying best practices, role-based access control (RBAC), and encryption. * Monitor and troubleshoot data workflows, ensuring performance, reliability, and cost-efficiency across Azure cloud environments. * Automate data integration and transformation tasks using Azure Functions, Logic Apps, and scripting languages like Python. * Mentor junior engineers and foster a collaborative team environment.   Essential Qualifications: * Bachelor’s degree in computer engineering, Computer Science, or a related discipline * Experience in ETL design, development, and performance tuning using the Microsoft Stack in a multi-dimensional data warehousing environment. * Advanced SQL programming expertise (PL/SQL, T-SQL) * Experience in Enterprise Data & Analytics solution architecture * Experience in Python Programming * Hands-on experience with Azure, especially for data-heavy/analytics applications leveraging relational and NoSQL databases, Data Warehousing, and Big Data solutions. * Experience with key Azure services: Azure Data Factory, Data Lake Gen2, Analysis Services, Databricks, Blob Storage, SQL Database, Cosmos DB, App Service, Logic Apps, and Functions * Experience designing data models aligning with business requirements and analytics needs. * Experience defining and implementing data security standards, including encryption, auditing, and monitoring. * Strong analytical skills and a passion for intellectual curiosity.   Preferred Skills: * Experience setting up and operating data