Open to opportunities

James Dolan

@jamesdolan

Message

I am a Senior Data Engineer specializing in real-time streaming, fraud detection, and multi-cloud platforms.

United States

Message

What I'm looking for

I'm seeking senior data-engineering roles building real-time, multi-cloud streaming platforms (fraud or personalization), collaborating with data scientists to improve model accuracy, reduce latency, and maintain strong compliance and observability.

I am a Senior Data Engineer with over 10 years building large-scale, real-time data systems across fintech, social media, and gaming. I design resilient streaming architectures and ETL pipelines using Kafka, Spark, Azure and GCP to drive low-latency insights.

At SAS I led fraud-detection pipelines processing billions of transactions with sub-second latency and improved detection accuracy by 25%; at Facebook I scaled Kafka and Dataflow pipelines to handle roughly 2 billion daily interactions and reduced model latency by ~40%. I partner closely with data scientists to deliver feature pipelines, improve observability, and ensure regulatory compliance (PCI DSS, GDPR, SOC 2).

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

SAS Institute

Nov 2021 - Present (3 years 9 months)

Led creation of real-time transaction ingestion pipelines processing over 10 million transactions daily with sub-second latency, enhancing SAS Fraud Management. Designed resilient streaming frameworks that cut data processing times by 30% and developed 150+ ETL pipelines supporting 50+ predictive models, improving fraud detection accuracy 25% and reducing false positives 20%.

Python Pyspark Apache Kafka Azure Data Factory ELK Stack Azure Event Hubs

Senior Data Engineer

Facebook (Meta)

Oct 2016 - Oct 2021 (5 years)

Spearheaded design and scaling of 50+ Kafka pipelines delivering roughly 2 billion daily interactions on GCP and integrated Protobuf/Thrift event logs from 100+ services. Architected Flink and Spark streaming solutions and feature pipelines with Dataflow and BigQuery to reduce model latency ~40% and boost engagement ~15%, while implementing GDPR-compliant data controls.

Apache Kafka Apache Flink Apache Spark Google Cloud Dataflow BigQuery Vertex AI Presto Parquet GCP

Data Engineer

Electronic Arts

Sep 2014 - Aug 2016 (1 year 11 months)

Built high-volume Kafka and RabbitMQ ingestion pipelines and real-time analytics with Apache Storm to process gameplay telemetry for global franchises, supporting millions of concurrent players. Developed SQL-based ETL and behavioral feature pipelines to improve matchmaking and retention modeling for live game tuning.