Platform Engineer IV – Data Services

Location: Denver, CO – Hybrid (3 Days Onsite / 2 Days Remote)

Job Overview

We are seeking an experienced Platform Engineer IV to design, build, and maintain scalable, secure, and reliable AWS infrastructure and data platform services.

The ideal candidate will have strong expertise in AWS, Infrastructure as Code, CI/CD, containerization, Python automation, networking, and production operations. This role will support data lake infrastructure, AI/ML workloads, agent runtime environments, and large-scale data services.

Key Responsibilities

Infrastructure & Data Lake

• Design and manage AWS infrastructure for data lake environments, including S3, Glue Data Catalog, Athena, and EMR.

• Manage cross-account connectivity, VPC networking, security groups, and IAM roles and policies.

• Build and maintain infrastructure for AI agent runtime environments and compute resources.

• Support deployment and operation of graph database infrastructure, including capacity planning and performance tuning.

• Implement Infrastructure as Code using Terraform and CloudFormation.

• Manage secrets, access controls, key rotation, and security compliance for cloud and on-premises integrations.

CI/CD & Deployments

• Build and maintain CI/CD pipelines using GitLab CI/CD, Docker, and Artifactory.

• Manage container lifecycle, including image builds, versioning, deployments, and rollback procedures.

• Automate deployment workflows across development, testing, and production environments.

• Support cross-account deployment and connectivity requirements.

Application Development & Automation

• Develop and maintain automation scripts, CLIs, small services, and utilities primarily using Python.

• Build integration code connecting data platforms with internal and external systems.

• Develop tooling for data ingestion, deployment, environment provisioning, and operational workflows.

• Work with REST APIs and cloud SDKs, including AWS SDK/Boto3.

Production Operations

• Ensure production environment stability through monitoring, alerting, and incident response.

• Maintain SLAs for data pipelines and platform services.

• Implement monitoring for deployed applications, including health checks, error rates, latency, and resource utilization.

• Coordinate with data engineering and platform teams on connectivity, firewall requests, and integration requirements.

• Support onboarding of new data sources, including storage provisioning, access controls, and compute requirements.

Required Skills & Experience

• 5+ years of experience in Platform Engineering, Infrastructure Engineering, Cloud Engineering, or related roles.

• Expert-level experience with AWS services, including EC2, S3, IAM, VPC, Glue, Athena, EMR, Secrets Manager, and CloudWatch.

• Strong experience with Terraform; CloudFormation experience is also acceptable.

• Experience managing cross-account AWS architectures.

• Experience with VPC Peering, AWS PrivateLink, and Transit Gateway.

• Strong knowledge of IAM policy design and least-privilege access.

• Hands-on experience with Docker and containerization.

• Experience with CI/CD pipelines, preferably GitLab CI/CD.

• Strong experience with Linux and shell scripting.

• Experience with monitoring and alerting tools such as CloudWatch, Prometheus, or Grafana.

• Strong understanding of networking fundamentals, including DNS, CIDR, NAT, firewalls, and security groups.

• Proficiency in Python or a comparable programming language.

• Strong software engineering fundamentals, including Git-based workflows, code reviews, modular design, dependency management, and documentation.

• Experience writing unit and integration tests.

• Experience integrating automated testing into CI/CD pipelines.

• Experience writing integration code using REST APIs and cloud SDKs.

• Strong communication and cross-functional collaboration skills.

Preferred Skills

• Experience with graph databases such as AWS Neptune or Neo4j.

• Experience with Apache Kafka or similar streaming platforms.

• Experience with Apache Spark, preferably Scala.

• Experience with Airflow or similar workflow orchestration tools.

• Familiarity with AI/ML infrastructure, including model serving and compute infrastructure.

• Experience with MLflow or similar artifact management platforms.

• Experience with Splunk integration.

• Experience developing and operating APIs or small services using FastAPI or Flask.

• Experience in telecommunications or large-scale network operations environments.

• AWS certifications such as AWS Solutions Architect or AWS DevOps Engineer.