Open to opportunities

Kevin Ross

@kevinross1

Staff Data Engineer specializing in large-scale streaming lakehouse platforms for experimentation and governed analytics.

United States

Message

What I'm looking for

I’m looking to lead cloud-native data modernization—real-time streaming, lakehouse architecture, and experimentation metrics—while partnering with ML/product/analytics to deliver governed, observable platforms on AWS/Azure/GCP.

I’m a Staff Data Engineer with 10+ years of experience building large-scale batch and streaming data platforms across e-commerce, healthcare, experimentation, and retail. I focus on petabyte-scale lakehouse architectures, real-time event processing, experimentation platforms, and cloud-native analytics ecosystems spanning AWS, Azure, and GCP.

At DoorDash, I power the Real-Time Experimentation & Metrics Platform for the experimentation ecosystem. I own the Kafka → Flink → Pinot → Snowflake data plane that processes 80B–110B+ experiment exposure events/day with sub-60 second freshness SLAs and 99.99% event delivery reliability—helping teams iterate faster across ranking, pricing, and fulfillment systems.

I architected a centralized Metrics Layer using Dagster, dbt, Snowflake, PySpark, and Flink, standardizing 1,500+ reusable metrics and attribution models. This reduced experiment analysis turnaround time by 10x and improved metric consistency across 200+ experimentation use cases, while low-latency streaming pipelines aggregating billions of events into 1-minute operational metrics reduced incident detection from 45 minutes to under 5 minutes.

I also build governed, observable systems with production-grade governance and observability frameworks, decreasing experiment-related data incidents by 45% and improving lineage visibility across 5,000+ production assets. I’ve partnered closely with ML, product, analytics, and platform engineering teams—mentoring 8+ engineers and applying infrastructure-as-code with Terraform and Kubernetes to improve deployment times by 60%—and I’ve led similar modernization work in healthcare (HIPAA/regulatory reporting) at CVS Health and real-time analytics and CDC pipelines at Best Buy and eBay.

Experience

Work history, roles, and key accomplishments

Current

Staff Data Engineer

Current

DoorDash

Mar 2023 - Present (3 years 4 months)

Owned DoorDash's real-time experimentation and metrics data plane, building Kafka→Flink→Pinot→Snowflake pipelines for experiment exposure events with sub-60 second freshness SLAs and high delivery reliability. Designed a centralized metrics layer and lakehouse architectures, and led governance/observability frameworks to improve metric consistency and reduce data incidents.

Lead Data Engineer

CVS Health

Oct 2020 - Feb 2023 (2 years 4 months)

Led engineering for the COVID-19 Testing & Vaccination data platform, delivering healthcare pipelines with CDC/state reporting SLA compliance in HIPAA-regulated environments. Built real-time ingestion and interoperability pipelines, implemented medallion lakehouse modeling, and delivered Spark/Flink transformation and governance/observability for regulated data quality.

Senior Data Engineer

Best Buy

Jan 2020 - Sep 2020 (8 months)

Modernized Best Buy's real-time analytics platform on Google Cloud, building streaming and CDC pipelines to support near real-time personalization and Customer_360 initiatives. Improved ingestion latency, implemented enterprise CDC into BigQuery, and optimized BigQuery performance to reduce costs and improve dashboard response times.

Google Cloud Pub Sub BigQuery Kafka Debezium Pyspark BigQuery Storage Write API Oracle MySQL Docker Upsert Processing Partitioning Clustering Materialized Views

Data Engineer

Best Buy

Jul 2018 - Dec 2019 (1 year 5 months)

Contributed to the migration from legacy Teradata/Hadoop to a cloud-native BigQuery lakehouse architecture on GCP, consolidating enterprise data domains for analytics and reporting. Built batch ETL pipelines, dimensional models, and orchestration/CI-CD workflows to improve pipeline SLA adherence and reduce manual reporting effort.

Google Cloud Cloud Storage Hadoop Hive BigQuery SQL Pyspark Dimensional Models Denormalized Reporting Tables Terraform Kubernetes Jenkins Tableau Power BI CI CD SLA

Data Analyst

eBay

Oct 2016 - Jun 2018 (1 year 8 months)

Supported the launch of eBay's personalized shopping “Interests” feed by building behavioral analytics pipelines for clickstream and search events. Developed batch and streaming ETL and monitoring to support personalization/recommendation analytics and reduce dashboard latency and pipeline failures.