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Christopher Fu

@christopherfu

Senior data engineer building ML-ready lakehouse and real-time personalization data platforms.

United States
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What I'm looking for

I’m looking for a role where I can build ML-ready data pipelines and lakehouse platforms—spanning batch and streaming ingestion, orchestration, and governance—so teams can deliver personalization, analytics, and machine learning products.

I build cloud-native data and AI platforms where ingestion, governance, and feature engineering all connect. At CVS Health, I led development of a logistics forecasting and personalization lakehouse platform, integrating clinical, operational, and customer data into medallion-style pipelines using Databricks, Delta Lake, and Microsoft Fabric.

I also engineered major capabilities at dbt Labs, including the Enterprise Semantic Layer Platform and Metadata & Lineage Intelligence, and contributed to AWS’s Enterprise Data Lake Accelerator Platform. Across these roles, I’ve built batch and streaming ML-ready data pipelines with Python, Spark, Kafka, Airflow, and Snowflake/BigQuery/Redshift, with data lineage, metadata, and fine-grained access control.

Experience

Work history, roles, and key accomplishments

dbt Labs logoDL

Senior Data Engineer

Jun 2020 - Jan 2023 (2 years 7 months)

Engineered major capabilities for dbt Labs' Enterprise Semantic Layer Platform and Metadata & Lineage Intelligence Platform, establishing governed metrics and centralized business definitions.

Microsoft logoMI

Data Analyst

Jul 2015 - Mar 2017 (1 year 8 months)

Developed and maintained the Customer Intelligence & Business Analytics Platform, creating Power BI, Excel, and SQL Server dashboards for customer engagement, retention, and revenue analysis.

Education

Degrees, certifications, and relevant coursework

University of California, Berkeley logoUB

University of California, Berkeley

Bachelor of Science, Computer Science

2011 - 2015

Bachelor of Science in Computer Science from the University of California, Berkeley from 2011 to 2015.

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