Open to opportunities

Sandy Lim

@sandylim1

Message

I build governed lakehouse and ML data platforms that improve reliability, speed, and cloud efficiency.

United States

Message

What I'm looking for

I'm looking to lead data platform, lakehouse, governance, and ML feature infrastructure initiatives where I can improve reliability, delivery speed, and cloud efficiency while mentoring engineers.

I've built enterprise lakehouse platforms, ML feature infrastructure, and governed data systems at DoorDash, Stripe, and Zendesk over 12 years.

At DoorDash, I architected a logistics lakehouse migration of 200+ Hive tables to Apache Iceberg on Amazon S3, cutting ETL runtimes by 45% and reducing schema-drift failures by 90%. I also built Project Fabricator, reducing ML feature deployment from two weeks to two days across 50+ production models.

I established data contracts, observability, and lineage for 200+ Tier-1 datasets across eight business domains, reducing data-quality incidents by 60%. I led Snowflake and Databricks optimization work that saved $1.2M annually while sustaining 99.95% SLA attainment.

Earlier, I built fraud feature pipelines and high-availability transaction processing at Stripe, and migrated Zendesk reporting systems from MySQL to Redshift for 10x faster analytical queries. I enjoy setting architecture standards, advancing federated governance, and mentoring senior engineers through complex platform decisions.

Experience

Work history, roles, and key accomplishments

Current

Staff Data Engineer

Current

DoorDash

Dec 2021 - Present (4 years 8 months)

Architected the logistics lakehouse migration, consolidating 200+ legacy Hive tables into Apache Iceberg on Amazon S3 using Spark, Glue, and dbt; reduced daily ETL runtimes by 45%, accelerated data freshness to T+15 minutes, and eliminated 90% of schema-drift failures across downstream ML pipelines. Directed a Snowflake and Databricks cost-optimization initiative, reducing annual cloud spend by $1