Aren Ramirez

April 2024 – Present

Collaborated with senior engineers to design and implement scalable, fault-tolerant and highly available infrastructure using Terraform and Ansible to support customer-facing applications.
Maintained microservices hosted on Azure AKS, managed via ArgoCD, to secure and support CI/CD pipelines including Jenkins, Azure Pipeline Agents, Terraform, and Ansible.
Optimized SQL database performance by reducing daily database queries from 20 million to 50,000, significantly reducing database throttling and P1 incidents.
Developed and maintained CI/CD pipelines utilizing Jenkins, Azure Pipelines, Terraform, and Ansible to automate provisioning, deployment, and monitoring workflows.
Built real-time monitoring and alerting solutions for cloud and on-prem environments, leveraging Python, GO, Splunk, CloudWatch and Nagios to enhance application visibility and incident response times.
Investigated and resolved production incidents, collaborating with NOC, DBOps, NetEng, and various SWE teams.
Proactively improved and took ownership of neglected services from the team. Wrapping them in automation, improving security, and writing documentation improving collaboration.
Introduced NPIs, working closely with other engineering teams and stakeholders to gather requirements, MVP, and timelines.

June 2021 – August 2021

Analyzed various datasets using Pandas, SQL, Python, and Machine Learning techniques. Generated informative visualizations (bar charts, line graphs, scatter plots, pie charts) to uncover insights.
Developed visualizations and metrics for a Spotify popularity project, enhancing team understanding of data patterns and trends.
Worked in a cross-functional team of three interns to analyze a dataset. Developed charts and maps illustrating data trends like reviewer popularity, top countries, and highest scores. Employed agile methodologies, including Scrum meetings and consistent communication with team lead.
Led a project exploring Spotify popularity trends. Implemented diverse machine learning models to visualize artist characteristics like energy and acousticness, and conducted analysis on audio features, top genres, and explicit content trends.

June 2019 – August 2019

Provided technical support for 100+ employees involving hardware and software issues through an internal ticketing system. Sustained ideal ticketing call rates greater than 80% team-wide.
Collaborated with desktop services team of 12 employees plus 4 interns in setting up company events. Assisted in setting up a company live stream for public viewing of board meetings.
Cooperated with team to image laptop/desktop systems and scheduled meetings with employees to deploy imaged systems.

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