Open to opportunities

Roy Asher

@royasher

Message

Principal data engineer delivering scalable lakehouse and real-time platforms.

United States

Message

What I'm looking for

I’m looking to lead cloud-native data engineering for AI-ready, real-time lakehouse platforms—prioritizing governance, security, reliability, and cost efficiency. I want a team where mentoring and measurable business impact are valued.

I’m a Principal Data Engineer with 10+ years of experience designing and delivering scalable, high-performance data platforms across E-Commerce, Healthcare, FinTech, and AI-driven environments. I build end-to-end cloud-native data ecosystems—real-time streaming and modern lakehouse solutions—leveraging AWS, Snowflake, and Databricks to enable advanced analytics and machine learning at scale.

I’m also deeply focused on reliability, scalability, and cost efficiency, translating business requirements into production-ready data products. From establishing enterprise-grade data governance and observability to optimizing large-scale pipelines and leading teams of 8 engineers, I consistently deliver measurable impact—like reducing infrastructure costs by 30%+ and improving accuracy and readiness across regulated environments.

Experience

Work history, roles, and key accomplishments

Current

Principal Data Analytics Engineer

Current

Veritone Analytics

Nov 2023 - Present (2 years 7 months)

Architected and delivered an AWS-based lakehouse and streaming platform supporting high-volume e-commerce analytics. Built event-driven ingestion with Kafka and Kinesis, optimized Spark/ETL workflows to cut infrastructure costs by 30%+, and led/mentored a team of 8 engineers.

AWS S3 AWS Glue Amazon Kinesis Apache Kafka Amazon Redshift Apache Spark Lakehouse Architecture Data Governance Event Driven Observability

Senior Data Engineer

Databricks

Jun 2021 - Sep 2023 (2 years 3 months)

Designed and implemented scalable ETL/ELT pipelines for enterprise analytics and AI workloads on Databricks. Built a centralized feature store, automated ML lifecycle processes with MLflow and CI/CD, and improved pipeline reliability and BI reporting accuracy.

Databricks Apache Spark Pyspark Delta Lake MLFlow Kafka CI CD Observability Data Modeling

Data Engineer

BlackBird Health

Apr 2018 - May 2021 (3 years 1 month)

Built HIPAA-compliant ETL pipelines integrating EHR/EMR and claims data to enable longitudinal patient analytics and secure clinical reporting. Improved data accuracy by 40%+ through automated validation and data quality frameworks while implementing encryption, access control, and audit-ready governance.

Data Quality Data Validation Encryption Access Control Data Governance Audit Readiness

Data Software Engineer

DailyPay

Mar 2016 - Feb 2018 (1 year 11 months)

Developed high-performance batch and streaming ETL pipelines for large-scale financial transaction systems, including real-time fraud detection and risk analytics. Migrated legacy workflows to scalable Spark-based distributed architectures and improved reconciliation accuracy and processing speed through optimized data pipelines.

Apache Spark Fraud Detection Risk & Analytics ETL Engineering API Integration