Manager -Data Engineer -AWS, Python, UI and Web Engineer-Agentic AI

Job Description

Ready to build the future with AI

At Genpact, we don't just keep up with technology-we set the pace. 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, 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 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 Manager -Data Engineer ( AWS, Python, Spark, Databricks for ETL-Agentic AI

In this role, you%27ll be part of Genpact%27s transformation under GenpactNext, as we lead the shift to Agentic AI Solutions-domain-specific, autonomous systems that redefine how we deliver value to clients. You%27ll help drive the adoption of innovations like the Genpact AP Suite in finance and accounting, with more Agentic AI products set to expand across service lines.

Responsibilities

- Design, develop, and manage scalable ETL pipelines using AWS Glue, Databricks, Apache Spark, and Python to process structured and unstructured data from diverse sources.

- Build and orchestrate data workflows integrating with services such as AWS Lambda, Step Functions, S3, and Redshift, ensuring high availability and performance.

- Optimize Spark jobs for performance and cost-efficiency across Databricks and AWS Glue environments using partitioning, job bookmarks, and dynamic frame operations.

- Maintain secure data solutions in AWS, leveraging IAM roles, KMS encryption, and VPC-based security to meet compliance and governance standards.

- Migrate legacy ETL jobs and data from on-prem systems to cloud-native architectures on AWS Glue, Redshift, and DynamoDB.

- Implement/monitor data pipeline performance, performing debugging and tuning of Spark jobs to ensure reliable execution and minimal downtime.

- Contribute in the design and review of technical solutions, translating business requirements and user stories into scalable data engineering architectures.

- Conduct unit testing and data validation to ensure functional correctness of pipelines before deployment.

- Contribute to production deployment and collaborate with release management to ensure seamless delivery of data solutions.

- Recommend cost-effective, secure, and high-performing cloud-based data solutions, reducing manual overhead and operational burden.

Qualifications we seek in you

Minimum Qualifications

- Experience in designing, implementing data pipelines, build data applications, data migration on AWS

- Strong experience of implementing data lake using AWS services like Glue, Lambda, Step, Redshift

- Experience of Databricks will be added advantage

- Strong experience in Python and SQL

- Proven expertise in AWS services such as S3, Lambda, Glue, EMR, and Redshift.

- Advanced programming skills in Python for data processing and automation.

- Hands-on experience with Apache Spark for large-scale data processing.

- Proficiency in SQL for data querying and transformation.

- Strong understanding of security principles and best practices for cloud-based environments.

- Experience with monitoring tools and implementing proactive measures to ensure system availability and performance.

- Excellent problem-solving skills and ability to troubleshoot complex issues in a distributed, cloud-based environment.

- Strong communication and collaboration skills to work effectively with cross-functional teams.

Preferred Qualifications/ Skills

- Bachelor's degree in business information systems (IS), computer science or related field, or equivalent-related IT experience.

- AWS Data Engineering & Cloud certifications, Databricks certifications

- Familiar with multiple data integration technologies and cloud platforms

- Knowledge of Change & Incident Management process

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