Ashutosh Gautam

Optimised data integration using Fivetran HVR, connecting diverse data sources to target systems while enhancing performance and reducing latency.
Built and maintained high-performance data pipelines, boosting data flow efficiency by 30% and improving reporting accuracy for critical business insights.
Automated server listener initiation through scripting, reducing manual effort, minimising downtime, and lowering incident tickets by 10%.
Resolved a critical PostgreSQL replication issue in HVR caused by irregular capture cycles by coordinating with the vendor and deploying a permanent heartbeat solution, reducing HVR-related incidents by ~20% and preventing WAL buildup.
Architected a comprehensive monitoring framework for HVR hub storage and jobs, achieving greater than 90% disk utilisation alert accuracy, oversized file detection greater than 10 GB, long-running job monitoring, and identification of suspended integrate jobs.
Streamlined HVR agent listener startup on source servers post-patching, decreasing manual intervention and cutting weekend incident tickets by 60%+.
Configured and managed SMTP-based alert notification systems on HVR 6 hub servers (DEV & PROD), ensuring reliable delivery of replication and monitoring alerts.
Engineered automated daily cleanup scripts to remove unused HVR replication channels (empty cycles), collaborating with Data Architects to validate usage and safely disable obsolete channels.
Configured HVR latency and error alerting for capture and integrate jobs with near real-time (hourly) notifications, enabling faster detection of replication delays and failures.
Authored a custom script to clean S3 buckets, streamlining maintenance processes and minimising cloud storage dependencies.
Recognised for improving data pipeline efficiency; selected to lead team workshops on HVR, enhancing team expertise and accelerating integration delivery.
Built S3-to-Databricks ingestion pipelines using Databricks Auto Loader, handling schema inference, incremental file processing, and scalable data loading.
Designed and deployed ETL pipelines using PySpark on Databricks, transforming large-scale structured and semi-structured data for analytics and downstream consumption.
Created PySpark jobs for data cleansing, deduplication, schema validation, and enrichment, improving data quality and consistency across target systems.
Optimised Spark transformations using partitioning, caching, and broadcast joins, reducing execution time and improving cluster efficiency.
Integrated HVR and Fivetran ingested data with Databricks for downstream processing and analytics use cases.
Implemented Change Data Capture (CDC) pipelines using Fivetran HVR (v5 & v6) with log-based replication for Oracle, PostgreSQL, and other RDBMS sources, enabling near real-time data movement to downstream systems.
Designed and managed real-time data replication architectures, ensuring low-latency, high-throughput, and transactional consistency across source and target systems.
Configured and maintained HVR hubs, agents, channels, and locations, supporting initial bulk load, incremental sync, and continuous CDC pipelines.
Worked extensively with HVR channel actions (Capture, Integrate, Refresh, Compare, Repair) to ensure data accuracy, reconciliation, and automated recovery.
Monitored and tuned CDC replication performance, improving pipeline efficiency by 30% through optimisation of capture/integrate jobs and system resource utilisation.
Handled schema evolution and DDL changes in HVR pipelines with minimal downstream impact, ensuring seamless replication continuity.
Developed monitoring and alerting frameworks for CDC pipelines (latency, failures, disk usage), achieving greater than 90% alert accuracy and faster incident resolution.
Performed data validation and reconciliation using compare/repair mechanisms to ensure data consistency between source and target systems.
Managed secure data replication practices, including encrypted communication, credential management, and controlled access for HVR environments.
Led internal workshops on CDC and HVR best practices, improving team adoption and delivery speed.
Root Cause Analysis (RCA) for all the failures in HVR and Issues.

Optimized data integration using Fivetran HVR, connecting diverse data sources to target systems while enhancing performance and reducing latency., Built and maintained high-performance data pipelines, boosting data flow efficiency by 30% and improving reporting accuracy for critical business insights., Automated server listener initiation through scripting, reducing manual effort, minimizing downtime, and lowering incident tickets by 10%., Resolved a critical PostgreSQL replication issue in HVR caused by irregular capture cycles by coordinating with the vendor and deploying a permanent heartbeat solution, reducing HVR-related incidents by ~20% and preventing WAL buildup., Architected a comprehensive monitoring framework for HVR hub storage and jobs, achieving greater than 90% disk utilization alert accuracy, oversized file detection greater than 10 GB, long-running job monitoring, and identification of suspended integrate jobs., Streamlined HVR agent listener startup on source servers post-patching, decreasing manual intervention and cutting weekend incident tickets by 60%+., Configured and managed SMTP-based alert notification systems on HVR 6 hub servers (DEV & PROD), ensuring reliable delivery of replication and monitoring alerts., Engineered automated daily cleanup scripts to remove unused HVR replication channels (empty cycles), collaborating with Data Architects to validate usage and safely disable obsolete channels., Configured HVR latency and error alerting for capture and integrate jobs with near real-time (hourly) notifications, enabling faster detection of replication delays and failures., Authored a custom script to clean S3 buckets, streamlining maintenance processes and minimizing cloud storage dependencies., Recognized for improving data pipeline efficiency; selected to lead team workshops on HVR, enhancing team expertise and accelerating integration delivery., Built S3-to-Databricks ingestion pipelines using Databricks Auto Loader, handling schema inference, incremental file processing, and scalable data loading., Designed and deployed ETL pipelines using PySpark on Databricks, transforming large-scale structured and semi-structured data for analytics and downstream consumption., Created PySpark jobs for data cleansing, deduplication, schema validation, and enrichment, improving data quality and consistency across target systems., Optimized Spark transformations using partitioning, caching, and broadcast joins, reducing execution time and improving cluster efficiency., Integrated HVR and Fivetran ingested data with Databricks for downstream processing and analytics use cases.

Implemented Change Data Capture (CDC) pipelines using Fivetran HVR (v5 & v6) with log-based replication for Oracle, PostgreSQL, and other RDBMS sources, enabling near real-time data movement to downstream systems., Designed and managed real-time data replication architectures, ensuring low-latency, high-throughput, and transactional consistency across source and target systems., Configured and maintained HVR hubs, agents, channels, and locations, supporting initial bulk load, incremental sync, and continuous CDC pipelines., Worked extensively with HVR channel actions (Capture, Integrate, Refresh, Compare, Repair) to ensure data accuracy, reconciliation, and automated recovery., Monitored and tuned CDC replication performance, improving pipeline efficiency by 30% through optimization of capture/integrate jobs and system resource utilization., Handled schema evolution and DDL changes in HVR pipelines with minimal downstream impact, ensuring seamless replication continuity., Developed monitoring and alerting frameworks for CDC pipelines (latency, failures, disk usage), achieving greater than 90% alert accuracy and faster incident resolution., Performed data validation and reconciliation using compare/repair mechanisms to ensure data consistency between source and target systems., Managed secure data replication practices, including encrypted communication, credential management, and controlled access for HVR environments., Led internal workshops on CDC and HVR best practices, improving team adoption and delivery speed., Root Cause Analysis (RCA) for all the failures in HVR and Issues.