Building Data and AI enabled products with an aim to be 1% better every day!

Contributing to Conversational Al Insights product with the help of various NLP and LLM and classification models with aim of improving contact centre experience and enabling Insights.

Gathering feedback for Pre-GA features from early adaptors of GCP enterprise customers and help improve the product as a part of the incubation team.

• Led a team that built a Snowflake based configuration driven and logging enabled Data Processing platform on AWS and Azure utilizing features like Stored Procedures, Data Exchange and Sharing, Fine Grain security and Airflow/ADF as orchestrator

• Bagged over 2 million USD in projects with multiple clients that ended up using the Snowflake and Databricks framework we created on AWS and Azure

• Incubated ideas and demos to destroy data silos and implement a Data Mesh that works with any cloud platform using Collibra as a Data Catalog, Starburst as a virtualization layer and Immuta for federated governance

• Managed task and project planning and mentored teams with HLD, LLD for building enterprise data ingestion and processing solutions using AWS (EMR/Glue with Airflow), Azure (Databricks with ADF) and Snowflake for Clients

• Improved performance existing Databricks pipeline on Azure by 30% using ADF, Azure Functions and Azure DevOps

• Led a team that built a Snowflake based configuration driven and logging enabled Data Processing platform on AWS and Azure utilizing features like Stored Procedures, Data Exchange and Sharing, Fine Grain security and Airflow/ADF as orchestrator Bagged over 2 million USD in projects with multiple clients that ended up using the Snowflake and Databricks framework we created on AWS and Azure Incubated ideas and demos to destroy data silos and implement a Data Mesh that works with any cloud platform using Collibra as a Data Catalog, Starburst as a virtualization layer and Immuta for federated governance Managed task and project planning and mentored teams with HLD, LLD for building enterprise data ingestion and processing solutions using AWS (EMR/Glue with Airflow), Azure (Databricks with ADF) and Snowflake for clients Improved performance existing Databricks pipeline on Azure by 30% using ADF, Azure Functions and Azure DevOps

Transformed the data landscape for multiple AWS based clients by building end to end enterprise big data ingestion and processing solutions using PySpark and SQL complex transformations and DQM validations.

Significantly contributed to Data modelling, STTM (source to target mapping), design documents for all client projects to ensure highest quality of deliverables

Bootstrapped ZS' findings on running Spark on EKS well before it was bundled with AWS as a part of R&D team. Also created monitoring dashboards for Spark jobs on EKS using Prometheus and Grafana

Migrated traditional on-prem ETL/ELT pipelines to AWS cloud using technologies like EMR for compute, RDS for audit, Airflow, Control - M for orchestration and S3/ADLS for storage, Dataiku for ML-Ops

Worked on developing a test bed for permissioned blockchain frameworks like Quorum, Hyperledger Fabric and Sawtooth. Also developed Ethereum light node on Raspberry Pi with wallet(s) flashed on Arduino(s).

Worked on recommendation system through AI on podcasting application and Developed a supply chain management application on BigChainDB, a Blockchain framework.