Sr. Principal Consultant – Big Data, Cloud Engineering

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 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 Sr. Principal Consultant – Big Data, Cloud Engineering

In this role, you will lead large-scale Quality Engineering initiatives across Big Data ecosystems, Cloud-based data platforms, and enterprise data warehouses. You will drive test strategy, data validation frameworks, and automation for high-volume, mission-critical systems, while collaborating with cross-functional engineering and product teams. You will also oversee quality governance, define data quality rules, optimize test methodology, and guide teams in delivering robust and scalable data engineering/ETL solutions.

Responsibilities

• Lead end-to-end QA strategy and execution for Hadoop, Google Cloud, AWS, and hybrid data engineering ecosystems.

  
  

• Analyze heterogeneous data sources and configure extraction/transformation logic in metadata-driven ETL/PL SQL/Hive frameworks.

  
  

• Drive validation of data pipelines across Hadoop, BigQuery, Bigtable, GCS, Redshift, Hive, Spark, and real-time ingestion platforms.

  
  

• Design and maintain test infrastructure enabling scalable validation for distributed systems and large datasets.

  
  

• Lead data profiling, data quality rule creation, and lineage documentation for enterprise warehouse/Data Lake initiatives.

  
  

• Oversee ETL, PL/SQL, API and Big Data testing activities including SIT/UAT, regression, performance, and production validation.

  
  

• Manage and mentor global QA teams; conduct reviews for scenarios, test cases, and automation scripts.

  
  

• Implement automation using Python/Shell scripting for regression and reporting workflows.

  
  

• Collaborate with cross‑functional stakeholders across US, India, Singapore and China for requirement clarification and defect triage.

  
  

• Optimize SQL queries, PL/SQL packages, Hive scripts, and data workflows for quality and performance.

  
  

• Prepare daily/weekly reports, manage project communication, and ensure adherence to Agile (SAFe) delivery frameworks.

  
  

Qualifications we seek in you!

Minimum Qualifications

• Extensive experience in Big Data QA, Cloud data engineering validation, ETL/PL SQL testing, and enterprise data quality.

  
  

• Strong hands-on expertise in Hadoop (Hive, HDFS, Spark, HBase, Sqoop, Flume), GCP (BigQuery, Bigtable, GCS), AWS (S3, Redshift, Glue).

  
  

• Proficient in SQL, PL/SQL, Unix, Shell scripting, Python, and data validation at scale.

  
  

• Experience with Agile/Scrum, CI/CD, and data testing tools such as Jenkins, Oozie, Control-M, Autosys, Rally, JIRA, QC.

  
  

• Proven experience validating end‑to‑end data ingestion, transformation and warehouse models (Star/Snowflake).

  
  

• Excellent analytical, communication, and stakeholder management skills.

  
  

Preferred Qualifications/ Skills

• Experience with real-time data pipelines using Kafka, Zookeeper, SQS.

  
  

• Strong understanding of healthcare domain (CVS, Aetna, BCBS, FCHP) and regulatory reporting.

  
  

• Expertise in metadata-driven frameworks and enterprise QA optimization.