F5 Networks acquired Threat Stack. Responsibilities include everything prior, plus:

Data Fabric team - led design and development of Iceberg and Delta Lake data platforms, using Apache Spark on both EMR and Databricks.

• Implemented a flexible authentication mechanism for ingesting telemetry and attributing it to a number of different products and teams within the company.

• Helping users design schemas and model their data, operate on it efficiently, and effectively gain insight into how customers are using the products they've deployed.

• Labeling and exporting of events to downstream systems for further analysis.

• Keeping Elasticsearch pleased and costs under control as required.

• Developing Avro / OpenTelemetry (OTEL) ingestion microservices in Scala / Go, data pipelines using Kafka and Spark and S3.

• Helping port aspects of our existing platform from Chef on EC2 to Kubernetes via Argo CD.

• Maintaining a number of data systems including Kafka, Druid, Spark, Elasticsearch, and Postgres, Akka.

Deep experience scaling distributed systems, optimizing databases, managing data lifecycle and helping data scientists and engineers get what they need, where and when they need it.

Backend services development, platform architecture design, and scaling the product to continually operate on an unrelenting stream of security telemetry.

Part of the team responsible for keeping customer installed agents connected to our platform and events flowing through the pipes in a timely manner. Navigated and lead recovery through many on-call incidents where this wasn’t the case. (lol)

Worked on every facet of the product including development and operation of: raw event search, data labeling with rules, alert generation, surfacing of anomalous events, automated reports, aggregating vulnerabilities, and delivering insight / analytics at scale.

Designed, implemented and maintained our S3 backed Data Platform, ingesting, enriching and transforming millions of events per second 24/7. Led development for subsequent features based on the core platform and services.

Tech Lead for Hot Search, Managed Rules, and Data Portability features. Team player always willing to lend a hand on-call. Scala Bootcamp instructor for new hires.

Generally speaking, just a little bit of everything, all of the time!

Data Store – A unified platform for scientific data in the organization

• Currently working on an Apache Spark and AWS based environment for supporting data science at NIBR

Intern Mentor: Project Mona Lisa – “A machine learning assisted diagramming tool”

• Mentored two interns on a platform for collecting hand drawn images, running machine learning algorithms on them to recognize what was drawn, and quickly suggesting high quality SVG replacements

• Trained a machine learning model with 94% accuracy for a set of commonly used images (network infrastructure diagrams, common shapes, computational biology items, etc.)

• Tools used: WAG stack (see below), Keras, Python, Flask, EC2, S3, DynamoDB, Jenkins, Nginx