Lead Consultant – Data Engineer.

Ready to shape the future of work? 

At Genpact, we don’t just adapt to change—we drive it. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory, our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies’ most complex challenges. 

If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that’s shaping the future, this is your moment. 

Genpact (NYSE: G) is anadvanced technology services and solutions company that deliverslastingvalue for leading enterprisesglobally.Through ourdeep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead.Powered by curiosity, courage, and innovation,our teamsimplementdata, technology, and AItocreate tomorrow, today.Get to know us atgenpact.comand onLinkedIn,X,YouTube, andFacebook.

Inviting applications for the role of Lead Consultant – Data Engineer.

In this role, a Data Engineer will leverage cloud technologies to manage and analyze their data. This role demands expertise in Databricks, Azure Data Factory (ADF), Python, PySpark and Unity Catalog to efficiently process and analyze large datasets. Data Engineer is responsible for designing and implementing scalable data pipelines, optimizing data workflows, ensuring data quality, collaborating with cross-functional teams, and leveraging cloud technologies to enhance data processing and analytics capabilities.

Responsibilities 

• Data Pipeline Design and Development:

  
  

• Architect, build, and optimize data ingestion and transformation pipelines using Azure ADF and Databricks.

  
  

• Implement data integration and transformation solutions using Azure Databricks.

  
  

• Develop and deploy data models and solutions using Azure services.

  
  

• Data Management and Optimization:

  
  

• Pull, ingest, transform, stitch, and wrangle data from various sources for advanced analytics.

  
  

• Design, implement, and deploy data loaders to load data into the engineering sandbox.

  
  

• Monitor and optimize data pipelines for performance and reliability.

  
  

• Collaboration and Support:

  
  

• Collaborate with cross-functional teams to gather requirements and understand data needs.

  
  

• Provide input to machine learning (ML) engineers and cloud engineers for designing and implementing data management or architecture solutions.

  
  

• Assist ML engineers in pulling, filtering, tagging, joining, parsing, and normalizing datasets.

  
  

• Data Quality and Security:

  
  

• Implement data quality checks, validation rules, and governance policies to ensure accuracy, reliability, and security of data assets.

  
  

• Troubleshoot and resolve data-related issues promptly.

  
  

• Implement data security and privacy measures to protect sensitive information.

  
  

• Implement Unity Catalog:

  
  

• Manage data governance and security using Unity Catalog to ensure compliance and protect sensitive information.

  
  

• ETL development:Develop scalable data ingestion or ETL from Workday and HR systems.

  
  

• Leverage data best practices and tools and assist ML engineer in pulling, filtering, tagging, joining, parsing, and normalizing data sets for use.

  
  

Qualifications We Seek in You! 

Minimum Qualifications / Skills 

• A bachelor’s degree in computer science, Information Technology, Business, or a related field is required