Ashish Jha

Leading the design and implementation of a Cloud Platform and Cloud Data Platform on Google Cloud. Delivered HLD/LLD designs and POC on GCP; migrated on-prem applications and data to GCP with minimal downtime; defined infrastructure as code with Terraform and Google Cloud Deployment Manager. Implemented monitoring with Stackdriver, Prometheus, and Grafana; created Python-based data processing and ETL tasks for Databricks; advised on cost management and optimized resource usage. Built data lake/Data warehouse patterns and supported cross-functional data integration and DevOps pipelines.

Provided end-to-end data architecture and ingestion architecture for a Data Lake solution. Mapped E2E DB designs and data ingestion architectures; migrated from SQL Server to BigQuery; leveraged GCP Dataproc, Cloud Functions, and BigQuery. Created metadata-driven frameworks with Azure DevOps and Azure Data Lake in multi-cloud contexts; defined governance patterns, data retention, and archival strategies; delivered POC and roadmaps to steering committees.

Streamlined the import of data from various sources into BigQuery; built and automated data processing workflows on GCP (BigQuery, Dataproc, Cloud Functions) to ensure efficient data handling and transformation. Implemented scalable data pipelines using Spark/Databricks; established data lake and data warehouse architectures; performance tuning for Spark/Impala/Hive clusters; integrated with IBM MQ; near real-time data streams using Spark Structured Streaming and Presto/Trino; CI/CD via Jenkins and GitHub; mentored teams on cloud best practices.