Rahul Anand

Principal Data Engineer with 11+ years of experience architecting cloud data platforms, data Lakehouse ecosystems, streaming pipelines, and executive analytics products across Google Cloud Platform, Amazon Web Services, BigQuery, dbt, Apache Kafka, Apache Spark, and Looker. Trusted by enterprise clients including Broadcom, Cornerstone OnDemand, EdCast, Beekin, UKW, TortExperts, Host Hotels, and Regions Bank to turn fragmented data estates into reliable, AI-ready platforms with measurable speed, cost, compliance, and business impact.

• Cloud data architecture: Designs production-grade GCP/AWS data ecosystems from ingestion through curated medallion layers, analytics marts, BI semantic models, and ML-ready feature layers.

• Performance engineering: Re-architects expensive BigQuery and Looker workloads through partitioning, clustering, materialized dbt models, query-plan reduction, and shift-left transformation design.

• Real-Time Streaming & CDC: Builds event-driven architectures using Confluent Kafka, CDC connectors, Cloud Functions, and BigQuery streaming — delivering sub-3-minute reporting refresh cycles for platforms processing millions of events daily.

• Performance Optimization & FinOps: Specialized in BigQuery performance engineering — partitioning, clustering, materialization, and Shift-Left pre-computation strategies that have cut query times from 150+ seconds to under 5 seconds, reduced bytes scanned by 90%, and slashed cloud compute costs by 60%+.

• Enterprise delivery: Leads concurrent client engagements across technology, EdTech, LegalTech, real estate, hospitality, and financial services with strong ownership of reliability, governance, and stakeholder outcomes.

• Data Modernization & Migration: Leads full-stack cloud migrations, from legacy SSIS/Oracle/SQL to modern Data Lakehouse architectures on GCP and AWS, with automated schema evolution, idempotent pipelines, and zero-downtime cutover.