Ruohan Liu
@ruohanliu
Senior Data Engineer specializing in large-scale data migrations, lakehouses, and streaming.
What I'm looking for
I am a Senior Data Engineer with 10 years of experience building large-scale data platforms across AWS, Azure, and GCP, specializing in Snowflake, Databricks, Spark, Kafka, Airflow and Delta Lake. I led migrations of tens of thousands of ETL workflows, delivered real-time fraud-detection and low-latency ML feature pipelines, and integrated hybrid lakehouse architectures while enforcing HIPAA and SOC2 governance.
I have driven measurable performance and cost improvements—45% faster queries and 50% lower compute in a major migration—built unified orchestration and CI/CD practices, mentored junior engineers, and delivered high-impact analytics (including a $586M health-waste analysis). I prioritize reliability, observability, secure data governance, and reproducible pipelines that meet strict SLAs.
Experience
Work history, roles, and key accomplishments
Senior Data Engineer
Uber
Nov 2022 - Present (2 years 11 months)
Led migration of 18,000 Hive ETL workflows to Spark SQL on Databricks, delivering 45% faster queries and 50% lower compute costs; built Airflow orchestration, real-time Kafka->Spark streaming pipelines, and Snowflake integrations to enable low-latency ML feature pipelines and multi-tenant analytics for 10K weekly users.
Senior Data Engineer / Developer
Milliman
Nov 2013 - Nov 2022 (9 years)
Scaled MedInsight analytics from on-prem SQL to Azure Databricks and ADF, processing billions of claims for 300 clients; built HIPAA/SOC2-compliant ETL with tokenization, encryption, governed semantic layer, and Delta Lake optimizations to reduce latency and costs.
Education
Degrees, certifications, and relevant coursework
Acumen, LLC
Data & Policy Analysis
2012 - 2013
Data & Policy Analyst II role involving engineering SAS, SQL, and Python pipelines for Medicaid claims and policy analysis.
Centre College
Bachelor's Degree, Mathematics; Computer Science
2008 - 2012
Bachelor's degree in Mathematics and Computer Science focused on quantitative analysis and data processing for policy and healthcare applications.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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