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Kyle Schoen

@kyleschoen

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Senior Data Engineer delivering scalable cloud-native data platforms and analytics-ready pipelines.

United States

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What I'm looking for

I seek senior engineering roles building scalable, cloud-native data platforms with strong emphasis on data quality, observability, and cross-functional impact.

I am a Senior Data Engineer with 10+ years building and scaling cloud-native data platforms across marketing, supply chain, growth, and IoT domains. I focus on delivering reliable, analytics-ready systems on AWS and Snowflake that inform high-impact business decisions.

I have led design and implementation of ELT/ETL pipelines, event-driven ingestion, and analytics engineering using Airflow, dbt, Terraform, AWS services, and streaming technologies. My work has powered marketing attribution, forecasting, and operational dashboards that support $100M+ decisions and improved data accuracy and observability across organizations.

I prioritize data quality, cost optimization, and mentorship—implementing governance, monitoring, and CI/CD to scale platforms and raise organizational data maturity while partnering cross-functionally with Data Science, Product, and Finance.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Instacart

Nov 2022 - Present (3 years 7 months)

Led design and launch of a Marketing Attribution Data Foundation on AWS, Snowflake, dbt, and Airflow that informed $100M+ annual marketing decisions and improved pipeline reliability and cost-efficiency.

AWS S3 Lambda ECS Snowflake DBT Airflow Terraform Data Modeling Observability

Senior Data Engineer

Dawn Foods

Sep 2019 - Nov 2022 (3 years 2 months)

Designed and delivered a Global Supply Chain Analytics Platform on Snowflake and Redshift powering 20+ KPIs, built inventory forecasting marts with 95% data accuracy and automated workflows to reduce manual intervention by 80%+.

Snowflake Amazon Redshift AWS Glue S3 DBT Airflow Data Governance

Senior Data Analyst

ThirdChannel

Mar 2018 - Sep 2019 (1 year 6 months)

Built hybrid ingestion pipelines across Azure and AWS to centralize retail IoT and partner data into a unified warehouse, increasing pipeline reliability and data quality by ~40% to enable standardized KPI reporting.

Azure Data Factory AWS Glue S3 Data Ingestion ETL Data Validation SQL Analytics Engineering Lake Formation

Data Analyst

Accu-Time Systems

Sep 2016 - Mar 2018 (1 year 6 months)

Designed time-series ingestion frameworks for biometric IoT devices and refactored a legacy monolith into modular Python/Docker microservices, enabling low-latency processing and identifying fixes that saved ~$2M annually.

AWS Lambda SQS Step Functions Python Docker Time Series SQL Microservices Root Cause Analysis

Education

Degrees, certifications, and relevant coursework

University of Washington

Master of Science, Applied Mathematics

2014 - 2015

Completed a Master of Science in Applied Mathematics with coursework and projects focused on quantitative methods relevant to data engineering and analytics.