Anand Gangoni

I architect enterprise data platforms that scale — and the teams that sustain them. Over 15 years, I've designed and delivered data infrastructure at companies where the stakes are high and the data volumes are massive: Albertsons Companies, Cisco, PIMCO, JPMorgan Chase, and Zuora. My work sits at the intersection of cloud-native architecture, real-time streaming, and emerging AI — translating complex technical strategy into platforms that business teams can actually rely on. At Albertsons Companies, I led the enterprise migration from Snowflake to BigQuery at petabyte scale, defining ingestion, transformation, and governance standards that reduced operating costs while improving query performance. I'm contributing to a generative AI and RAG-enabled data platform that cut operational incident response time by 55% — one of the more tangible AI ROI outcomes I've seen in production. My technical foundation spans the full modern data stack — GCP, AWS, Azure, Kafka, Spark, Flink, Airflow, Dataflow — but what I care most about is architecture that holds up over time: governed, observable, cost-efficient, and built to evolve. Beyond the tech, I've spent years building the people side of data engineering — hiring 10+ engineers, mentoring leads, and partnering with executives to align platform roadmaps with business strategy. I specialize in building and scaling data platforms — architecting greenfield systems, modernizing existing ones, and structuring the teams to sustain them. Core focus areas: Cloud Data Architecture · Real-Time Streaming Pipelines · Data Governance & Lineage · Generative AI / RAG Platforms · Lakehouse & Warehouse Design · Data Platform Leadership