Last Updated on 15th November 2025
Jordan Moore
https://www.linkedin.com/in/jordanmoorerhit/
EXPERTISE
CLOUD
S3 • VPC • IAM • CloudWatch
• Route53 • EC2 • EKS •
CodeBuild • ECR • EMR
MICROSERVICES
Docker • Kubernetes • Mesos +
Marathon • Nomad • Consul • Vault
DATABASES
MongoDB • MySQL • Neo4j •
Cassandra • ELK Stack
CI/CD
ArgoCD, Events, & Workows •
GitHub Actions • Ansible • Puppet •
Terraform • Jenkins • Vagrant
APACHE PROJECTS
Hadoop • Spark • Hive • Kafka •
Avro • Impala
SKILLS
ENVIRONMENTS
Backend • APIs • Tool Development
• Data Analysis • Architecture •
Platform Engineering
PROGRAMMING
Java, Scala • Maven, Gradle, SBT •
JAX-RS • Dropwizard • Spring-MVC
• Jackson • Lombok
FastAPI • Flask • Requests •
Beautifulsoup • Pydantic
Go • NodeJS • HTML,CSS,JS • PHP
• Android
EDUCATION
ROSE-HULMAN INSTITUTE
OF TECHNOLOGY
Double Major in Software
Engineering and Computer
Science
Minor in Mathematics and
Computational Science
EXPERIENCE
ADOBE SYSTEMS INC.
• Built Adobe Cloud Platform tooling and extensions as part of an Internal Developer
Platform (IDP)
• Performed support & on-call services for internal Cloud Platform clients
• Maintained scalable, multi-tenant software templates for use across business units
• Advocated for container-based CI/CD and Development workows via hands-on
training
> DEVELOPER PLATFORMS
• Feature development for Adobe Cloud Services Platform on Kubernetes,
overseeing an ecosystem of hundreds of clusters
• Deected over 25% of support tickets with a Python-based RAG GPT chatbot
built with LLM tokens from internal docs
• Implemented Golang tooling to migrate managed applications between ArgoCD
instances
• Developed Backstage Templates and Actions to automated zero-to-production
developer onboarding
> MAGENTO
• Developed Commerce Cloud administration plugins within Adobe Experience
Cloud using Node
• Led development of Commerce Cloud Golang HTTP Provider and Terraform
Provider
• Enhanced monitoring capabilities of Magento PWA Studio & AEM Cloud
Manager with Prometheus + Grafana
• Improved JUnit test-suite runtime for AEM Cloud Manager by 85+%
INSPIRED INTELLECT
• Engineered Big Data, event-driven architectures, microservices, and Kafka
environments for clients
• Created pre-sales demos using Vagrant, Terraform, Docker orchestration, in
combination with Ansible and Bash
• Demonstrated analytical and log-parsing abilities utilizing Elasticsearch, Logstash,
and Kibana
> CLOUD DEVOPS & RELIABILITY ENGINEER
• Developed an AZ-Aware multi-cloud system capable of abstracting popular
Docker schedulers including Marathon, Nomad, and Kubernetes
• Migrated Apache Mesos workloads to Nomad, and then to Kubernetes
> HADOOP & KAFKA ADMINISTRATOR
• Administered and maintained a hybrid-cloud environment with a 100+ node
on-premise Hadoop cluster, multiple Kafka clusters within a multi-cloud
environments for a vacation-rental client
• Provided on-call support for infrastructure and developer questions, maintenance
notications, and debugging sessions
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Jordan Moore
https://www.linkedin.com/in/jordanmoorerhit/
EXPERIENCE (CONT.)
> HADOOP DATA WAREHOUSE OFFLOADER
• Converted plaintext Oracle database exports into Apache Parquet using Apache Pig
scripts for an international retail client
• Improved runtime of the client’s Oracle Pro*C ETL process by 90% using Apache
Impala and Parquet
> APACHE SPARK STREAMING DEVELOPER
• Built a Spark Streaming ETL pipeline for a multi-national payment processing client
• Wrote custom Hadoop InputFormats with regex support to parse semi-structured
documents into Spark RDDs
• Utilized Apache Hive, MemSQL, and ElasticSearch to query for payment transaction
details
> GRAPH DATABASE ANALYST
• Translated tabular data into into a format more suitable for a graph for a worldwide
technology client
• Compared Neo4j and OrientDB graph database abilities
• Presented both technologies as a solution for identifying connected components of
the client’s web trafc metadata to achieve targeted advertising
> APACHE SPARK MLLIB DEVELOPER
• Rened an iterative Random Forest algorithm to categorize transcribed call-center
issues for a worldwide technology client
• Developed a machine-learning model that achieved the client’s goal with 80+%
accuracy
• Manually tuned machine-learning model parameters to improve results
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