Kalan Barnes
Richardson
Summary
Results-driven AWS Platform Engineer with over 3 years of experience in designing and managing scalable, secure cloud platforms on AWS. Expertise in infrastructure-as-code, CI/CD automation, and data platform reliability, including production-grade EMR and Spark platforms. Proven track record of solving 300+ complex AWS infrastructure cases with a 95% CSAT, while implementing Terraform-based landing zones that reduced job execution time by 40%. AWS Certified Solutions Architect Professional and DevOps Engineer Professional.
Overview
4
4
years of professional experience
Work History
Cloud Support Engineer
Amazon Web Services
06.2024 - Current
- Provide advanced technical support for AWS customers running production big data platforms, specializing in EMR, Spark, Hadoop, Iceberg, and distributed storage.
- Diagnose and resolve complex infrastructure and application-level failures using YARN, Spark, HDFS, and EMR control-plane logs.
- Advise customers on secure and scalable data platform architectures using Glue, Lake Formation, IAM, and S3.
- Collaborate with internal AWS service teams to escalate and resolve service-impacting issues.
- Resolved 1000+ high-complexity cases with a consistent 95% CSAT, often involving multi-layer failures across networking, IAM, and compute.
Platform Engineer
Digital Mavens Technologies
03.2022 - 03.2024
- Designed and operated AWS-based internal platforms enabling application and data teams to deploy infrastructure safely and consistently without direct console access.
- Built Terraform-based landing zone infrastructure, including VPCs, private subnets, routing, IAM roles, and security boundaries across multiple environments.
- Developed reusable Terraform modules (networking, IAM, compute, storage) to standardize infrastructure provisioning and reduce configuration drift.
- Implemented security guardrails using least-privilege IAM policies, private networking, and VPC endpoints (S3, SSM, STS) to minimize blast radius.
- Created CI/CD pipelines for infrastructure using GitHub Actions and Terraform workflows (fmt, validate, plan, apply) to enforce safe change management.
- Supported data platform workloads by provisioning and optimizing EMR clusters, Spark jobs, and S3-backed data lake architectures.
- Partnered with engineering teams to abstract AWS complexity while ensuring scalability, compliance, and operational reliability.
- Improved cost efficiency by ~20% through rightsizing, lifecycle policies, and usage analysis using AWS Cost Explorer and architectural reviews.
Education
Bachelor of Science - Computer Science
Southern New Hampshire University
Hooksett, NH12-2024
Skills
- Automated EMR Platform with Terraform
- Designed and provisioned a production-grade EMR platform using Terraform, managing networking, IAM, and compute declaratively
- Configured private subnets, VPC endpoints, and secure role-based access for Spark and Hive workloads
- Modularized Terraform code and stored state securely in S3 with DynamoDB locking
- Automated post-deployment validation using SparkPi jobs to verify cluster health Scalable Data Platform on EMR
- Built an end-to-end Spark-based ETL platform processing 10M records from the Olist Brazilian e-commerce dataset
- Joined and enriched datasets using PySpark and optimized performance via partitioning and parallelism
- Orchestrated pipelines with AWS Step Functions and Glue Data Catalog integration Apache Iceberg Platform on EMR Serverless
- Deployed an Iceberg-backed lakehouse platform using Spark on EMR Serverless
- Enabled snapshot-based time travel, schema evolution, compaction, and orphan file cleanup
- Integrated with Athena and Redshift Spectrum for low-latency analytics
- Secured fine-grained access via Lake Formation and validated data lineage via Iceberg metadata SKILLS Platform Engineering
- Platform Engineering Principles
- Infrastructure as Code (Terraform)
- AWS Landing Zones
- Self-Service Infrastructure
- Environment Parity (Dev / Staging / Prod)
- IAM Guardrails & Security Boundaries AWS & Cloud
- VPC, Private Subnets, VPC Endpoints
- EC2, S3, EMR (EC2 & Serverless)
- AWS Glue, Lake Formation
- CloudWatch, Logging, Monitoring CI/CD & Automation
- GitHub Actions
- Terraform CI Pipelines
- GitOps Concepts
- Python, Bash Data Platforms
- Apache Spark
- Apache Iceberg
- Hadoop
- Data Lake & Lakehouse Architecture CERTIFICATIONS
- AWS Solutions Architect – Associate
- AWS Solutions Architect – Professional
- AWS DevOps Engineer – Professional
- AWS Data Engineer – Associate
Timeline
Cloud Support Engineer
Amazon Web Services
06.2024 - Current
Platform Engineer
Digital Mavens Technologies
03.2022 - 03.2024
Bachelor of Science - Computer Science
Southern New Hampshire University