I am Nitin Srivastava—a Principal Architect with 18+ years leading enterprise Databricks Lakehouse rollouts, building Medallion Architecture (Bronze/Silver/Gold), Unified Enterprise Data Models, EDW modernizations, and production Governance, Lineage & Quality.
Architecture
EDW, Lakes & Governance
End-to-end architecture advisory covering migration, platform engineering, data democratization, modeling, and active governance.
Architecting enterprise data lakes with Medallion architecture (Bronze ingestion, Silver curation, Gold business aggregates) powered by Databricks Delta Lake.
Designing canonical enterprise data models, Unified IAM/Identity schemas, Kimball dimensional star/snowflake models, and Data Vault 2.0.
Metadata-driven modernization transitioning legacy Teradata, Netezza, and SQL Server warehouses to scalable cloud-native architectures at petabyte scale.
Architecting resilient, serverless, and distributed data pipelines utilizing Amazon Redshift, AWS Glue, EMR, S3, and distributed PySpark.
Building self-service democratization platforms that transform centralized data bottlenecks into autonomous, discoverable domain data products.
Establishing governance-by-design, Collibra metadata management, column-level lineage, and PyDeequ statistical testing at petabyte scale.
Book an exploratory advisory session to discuss your data warehouse, lake, or governance roadmap.
Real-world SaaS applications and developer utilities engineered to solve high-friction data modeling and engineering problems.
AI-first enterprise data modeling studio, schema relationship visualizer, and Databricks Delta Lake DDL generation engine.
Transform raw technical work history into structured, high-impact STAR behavioral interview answers and curated examples for leadership roles.
Calculate optimal driver/executor memory, CPU core allocations, and partition sizing to stop PySpark OOM errors.
Curated architectural reference models, dimensional schemas, and enterprise SQL query optimization playbooks.
I specialize in designing resilient, production-hardened data ecosystems where robust data modeling, Data as a Product, automated lineage, and governance-by-design replace brittle pipelines and data silos.
Across 18+ years, I have architected automated migration engines for 4,000+ database objects, engineered petabyte-scale data validation frameworks, accelerated analytics delivery by 60%, and saved global enterprises $1.2M+ in annual cloud compute waste.
Automated transformation from Teradata, Netezza, DB2, and SQL Server to modern cloud architectures.
Amazon Redshift, AWS Glue, EMR, S3, Databricks Delta Lake, and PySpark distributed workloads.
Domain-driven Data Mesh, semantic layers, and self-service analytics democratization platforms.
Unity Catalog, Collibra metadata, automated lineage, PyDeequ quality testing & schema enforcement.
Sharing production-grade engineering blueprints, architectural patterns, and video masterclasses with the global data community.
Watch 100+ masterclasses covering SQL execution plans, PySpark distributed optimizations, and cloud Lakehouse migration validation patterns.
Explore Masterclasses on YouTubeInteractive architectural guides for dimensional schemas, window functions, and query optimization.
Whether you are planning a petabyte-scale warehouse migration, rolling out a Databricks Lakehouse, or seeking fractional data architecture leadership.