Jagadeesh Thiruveedula
Executive Summary
GCP Data Architect with 11+ years designing enterprise data platforms and leading large-scale cloud modernization on GCP. Deep expertise in Snowflake→BigQuery, Teradata→BigQuery, Hadoop→GCP, and Couchbase→Spanner/Bigtable migrations, enterprise warehouse design, SCD2, SQL optimization, and streaming architectures. Delivered $2M+ cost savings via FinOps practices, 500+ TiB migrations, and 1B+ daily events at 99.9% uptime. Combines architecture governance, stakeholder communication, and hands-on delivery with GenAI-accelerated migration tooling to cut delivery timelines and de-risk enterprise cutovers. Customer-facing architect with discovery workshops, pre-sales, and RFP/RFI experience across healthcare, insurance, energy, and publishing sectors.
Impact Highlights
Core Competencies
Professional Experience
- Snowflake → BigQuery Migration · 500+ TiB Led discovery workshops with platform and editorial leadership; architected GenAI-accelerated schema-mapping and SQL-translation pipeline cutting manual refactoring 40%; zero data loss across 200+ ETL workflows on Cloud Composer + Dataflow.
- Enterprise Warehouse Redesign · BigQuery Redesigned dimensional model and partitioning strategy for 50M+ document corpus; implemented SCD2 patterns and SQL optimization reducing query cost and improving analyst throughput 3x.
- Streaming & Real-Time Analytics · Pub/Sub + Dataflow Built event-driven pipelines for editorial telemetry; standardized CDC patterns and data-quality gates ensuring 99.9% uptime and audit-ready lineage.
- GenAI Migration Accelerators Codified reusable schema-mapping, query-translation, and validation patterns into an internal platform playbook adopted by 3 downstream programs; mentored 4 engineers.
- Embedded with mainframe operations; ran discovery across 12 COBOL/legacy workstreams to prioritize migration sequencing by risk and value.
- Built GenAI-powered code-translation pipeline (Mainframe/COBOL → BigQuery SQL + PySpark) with semantic-fidelity eval harness; deployed into customer GCP VPC behind their IAM.
- Designed high-throughput PySpark + BigQuery + Pub/Sub pipelines for batch + real-time streaming; refactored legacy logic into modern, audit-ready, anomaly-resistant patterns.
- Mentored customer engineering team on AI-assisted modernization; codified 5 reusable transformation patterns into the internal platform playbook.
- Embedded with energy operations analytics; scoped cross-cloud migration with phased cutover plan for near-zero downtime.
- Directed AWS data lake → GCP Databricks migration; built cross-cloud ingestion + transformation pipelines integrating BigQuery and Vertex AI for predictive maintenance models. Applied FinOps practices to optimize cross-cloud compute and storage spend.
- Delivered phased cutover with <30 min downtime; unified cost analytics pipeline reduced energy-trading reporting latency by 40% and improved uptime SLA adherence to 99.95%.
- Built Generative AI accelerators automating Talend ETL + SQL → PySpark conversion — 50% cut in delivery timelines; codified as reusable framework adopted across 10+ programs.
- Migrated 100+ TB on-prem warehouses & data lakes to GCP under HIPAA compliance; reduced infra costs and boosted ETL performance 30%.
- Architected real-time streaming (Kafka + Pub/Sub) for 50+ data sources; ensured 100% data accuracy and audit compliance under healthcare governance.
- Led design reviews; standardized AI-assisted coding tools; mentored 5 junior engineers to senior roles.
- Led multi-Petabyte Hadoop/Teradata → GCP migration; improved system speed & efficiency 25%; delivered $1M+ annual infra savings.
- Rewrote/optimized ETL with PySpark + Talend processing 1B+ daily records, zero data loss; standardized CDC patterns cutting pipeline dev time 40%.
- Built high-throughput transactional framework (PySpark + Qlik Replicate) processing 30M records/day at 99.5% SLA; automated monitoring cut data errors 15%.
- Established IaC (Terraform + Bitbucket + Bamboo) for metadata-driven BigQuery deployments, cutting release cycles 50%; featured in Free Press Journal (May 2025) for cloud-native frameworks adopted across 10+ enterprise programs.
- Built cloud-native mortgage recovery warehousing solution integrating Mainframe, Teradata, and NAS into a unified analytics platform.
- Developed scalable Talend Big Data streaming jobs; built reusable frameworks for file capture, SCD ingestion, snapshot ingestion, DQ checks, and Mainframe header validation adopted across the MARS team.
- Designed and developed 20+ ETL pipelines for the CROMA warehouse using Talend and PL/SQL; built fact/dimension models processing 5M+ records/day with automated data-quality checks reducing defect rates by 25%.
- Established reusable extraction, validation, and error-handling patterns adopted across 4 warehouse workstreams; cut new pipeline development time by 35% through framework standardization.
Education
Certifications & Languages
- Google Cloud Professional Data Engineer (GCP PDE)
- Talend Data Explorer
- Spark Certified Hadoop Developer