Technical Lead

• Directed a team of four developers to build a fully containerized, integrated knowledge graph application that reduced root problem diagnosis time by 45%, leveraging Docker, OrientDB, Elasticsearch, Node.js, and React.

• Led a team of seven developers to create a fully containerized Installation Verification Tool, reducing

deployment time by 20%, decreasing client reversal by 15%, and enhancing customer installation

experience, using Docker, Bash, and Python.

Software Engineer, Band 7

• Developed a message rarity feature using Python's machine learning libraries, decreasing false positive

anomalies detection by 61% and achieving a 35% reduction in root problem diagnosis >me.

• Modified product data architecture from indexes to data streams via Elastic stack, Opensearch, and Python,

increasing shard efficiency and search times by 30%.

• Automated product installation and deployment for an innovation project using Ansible and Jenkins,

reducing install and deploy time by 50% for developers and testers.

• Enhanced Opensearch’s alerting plugin to enable alerting capabilities on cloud based applications through Kotlin and JavaScript.

• Automated vulnerability scanning in source control by integrating Jenkins with container and static scan

processes.

• Containerized python based applications into services using Docker reducing setup time by 30% and

improving overall user satisfaction with the deployment process

Software Engineer, Band 6

• Built an end-to-end demo environment and app with Python and Flask to demonstrate the product’s

anomaly detection and prediction capabilities.

• Developed backend infrastructure for IBM’s workload visualizer using Node.js, enhancing visualization

capabilities for complex workloads.

• Worked with agile development

• Created a full stack SIEM app that extends and accommodate alternative data analysis tools

• Worked with Splunk’s Machine Learning capabilities to analyze and visualize zMainframe data

• Created advanced Splunk Apps to run custom scripts

• Managed continuous integration and deployment with Travis CI and Docker.

• Used Agile methodologies

• Engineered algorithms to increase query speeds of big data

• Used Scala, Hive, and Spark to analyze data sets

• Received files from TOPs Installation Reporting tool and removed unnecessary columns from raw files

• Created table extracts to change the live connection from hive to tableau (data visualization tool) to a static connection

• Removing data from raw files and creating extracts increased query speeds by over 160%.

• Wrote queries to retrieve data from Elastic Search, then developed and implemented Machine Learning algorithms that increased the speed of statistic calculations by 200%.

• Assisted the Cyber Security department and wrote events in Python that detected suspicious email activity.