Lead 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 an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep 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 teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.  
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: 
o    Architect, build, and optimize data ingestion and transformation pipelines using Azure ADF and Databricks. 
o    Implement data integration and transformation solutions using Azure Databricks. 
o    Develop and deploy data models and solutions using Azure services. 
•    Data Management and Optimization: 
o    Pull, ingest, transform, stitch, and wrangle data from various sources for advanced analytics. 
o    Design, implement, and deploy data loaders to load data into the engineering sandbox. 
o    Monitor and optimize data pipelines for performance and reliability. 
•    Collaboration and Support: 
o    Collaborate with cross-functional teams to gather requirements and understand data needs. 
o    Provide input to machine learning (ML) engineers and cloud engineers for designing and implementing data management or architecture solutions. 
o    Assist ML engineers in pulling, filtering, tagging, joining, parsing, and normalizing datasets. 
•    Data Quality and Security: 
o    Implement data quality checks, validation rules, and governance policies to ensure accuracy, reliability, and security of data assets. 
o    Troubleshoot and resolve data-related issues promptly. 
o    Implement data security and privacy measures to protect sensitive information. 
•    Implement Unity Catalog:  
o    Manage data governance and security using Unity Catalog to ensure compliance and protect sensitive information. 
o    ETL development: Develop scalable data ingestion or ETL from Workday and HR systems. 
o    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  
•    Experience in Databricks, Azure ADF, Python, Pyspark and Unity Catalog 
•    Experience in working on data ingestion or ETL from Workday or any other HR systems 
•    Experience in RBAC security models in Unity Catalog 
•    Exposure to CI/CD DevOps practices 
•    Experience with PySpark and SQL for building scalable data transformation jobs, data querying, analysis, and data modelling 
•    Expertise in Azure Databricks, including its features for big data processing and collaborative notebooks. 
•    Strong programming skills in Python for data manipulation and scripting. 
•    Proficiency in data engineering tools like Databricks, Apache Spark, and Unity Catalogue 
•    Hands-on experience with Azure Data Factory for pipeline orchestration, scheduling, and monitoring

Preferred Qualifications / Skills 
•    Certifications in Azure data engineering or related fields.

Why join Genpact?  
•    Be a transformation leader – Work at the cutting edge of AI, automation, and digital innovation  
•    Make an impact – Drive change for global enterprises and solve business challenges that matter  
•    Accelerate your career – Get hands-on experience, mentorship, and continuous learning opportunities  
•    Work with the best – Join 140,000+ bold thinkers and problem-solvers who push boundaries every day  
•    Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress  
Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up.  
Let’s build tomorrow together.    
Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation.   
Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.