Ravi Katiyar

• Services & Rate Recommendations:Developed and owned a rate recommendation service that suggests optimal rates for supplier discount offers. This has a direct revenue impact for the company. Designed and executed A/B experiments to improve the service's recommendation accuracy.
• Data Engineering & MLOps:Led the integration and productionalization of machine learning models in collaboration with the data science team.
  Implemented and maintained machine learning workflows using AWS technologies such as SageMaker, SageMaker Feature Store, batch inference jobs, and Redshift.
  Established robust CI/CD pipelines for model deployment and built scalable infrastructure using Airflow, Terraform and Kubernetes.
• Tech Stack & Tooling: Extensively used Python, Flask, SqlAlchemy, and Alembic for backend development, with Docker, Gunicorn, and Gevent for containerization and server management.
  Managed databases and data warehouses using Postgres, Redshift, and DBT, implementing data pipelines and ETL processes. K6.io for performance testing and Split.io for feature flag management. Deployed serverless functions and built microservices using AWS Lambda, and S3.
• Monitoring & Observability: Implemented comprehensive monitoring solutions with DataDog to ensure system stability and performance. Conducted regular shadow testing and utilized feature flags for controlled model deployments.
• Leadership & Mentoring: Mentored junior engineers, providing guidance on best practices and helping them grow their technical skills.
  Participated in interview panels, contributing to the selection and onboarding of new team members.
  

• Enterprise Data platform cloud migration
• Taking the responsibility of the batch and streaming pipeline which are on prem currently and have to migrated to cloud.
• Design consideration, evaluation of cloud technologies and migration plan and development.

• INFOEDGE-DATA-LAKE
• This is the central data platform of entire Infoedge.Our role is to collect all kind of data including user behavioural data,transactional data and provide computation and querying mechanism on collected data.
• 210 million messages processed daily.
• Build view and summaries using scala spark jobs to aggregate and summarize frequently required data.
• INSIGHTS.NAUKRI.COM
• The role of insights team in Naukri is to draw insights from data and build data products.Job seeker data of over 80 million job seekers provides us a big opportunity to perform analytics and make data driven business decisions.
• Technologies used includes spring rest,apache spark,elastic search,apache zeppelin,react js,redis.

Responsible for design and development of backend processes and web services for mobile application called ALIVE as well as internal CMS using core Java , Restful web services,Spring , Hibernate.

Worked on Amex hotline IVR system as java and IVR developer.

Worked on product called Caller Ring back tone (CRBT).