AI-Enabled AWS Data Lake Platform Developer

This remote Cloud Platform engineering role enables AWS Data Lake initiatives by designing, automating, and operationalizing secure, reusable cloud infrastructure.

The position partners with Data Engineering teams to deliver Terraform-based platform capabilities, GitHub-driven automation, and AI-assisted engineering practices that accelerate delivery while maintaining enterprise security, governance, operational excellence, and outstanding developer experience.

The AI-Enabled AWS Data Lake Platform Developer enables Data Lake solutions to run securely, reliably, and efficiently in AWS. The role translates Data Engineering requirements into reusable AWS infrastructure patterns, Terraform modules, GitHub-based automation, policy guardrails, and operational practices that align with Cloud Platform standards while improving consistency, scalability, and developer productivity.

Responsibilities

• Participate in Data Engineering team projects as the Cloud Platform engineering representative for AWS infrastructure enablement.
• Design, code, review, test, and maintain Terraform for AWS Data Lake infrastructure using GitHub repositories and pull requests.
• Build reusable patterns for S3 storage zones, IAM roles and policies, KMS encryption, networking, observability, and environment deployment.
• Use GitHub Actions, GitHub Packages, and GitHub Copilot-assisted workflows to support delivery, testing, documentation, and troubleshooting.
• Review and validate AI-assisted outputs before use in production or shared platform repositories.
• Embed security, compliance, tagging, naming, logging, monitoring, and operational standards into reusable infrastructure patterns.
• Create documentation, handoff notes, runbooks, and support guidance for deployed Data Lake capabilities.
• Continuously improve reusable Terraform modules, platform capabilities, and engineering standards based on operational feedback and evolving AWS services.
• Enable Data Engineering teams through reusable infrastructure patterns, documentation, onboarding guidance, and self-service platform capabilities.
• Partner with Data Engineering teams to optimize AWS infrastructure for cost, performance, scalability, resilience, and operational efficiency.
• Contribute to the evolution of Cloud Platform standards, reusable modules, golden paths, and internal developer experience.

Work Schedule:

• This position is remote
• Domestic travel may be required.
• Must be willing and able to work after hours and provide on-call support as needed.

Qualifications

• Education:

+ Required: Practical experience in cloud infrastructure engineering, platform engineering, data platform enablement, application development, or related technical delivery roles. + Preferred: Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Engineering, or equivalent technical experience.

• Experience:

+ 5+ years of relevant cloud infrastructure, platform engineering, DevOps, data platform, or related technical delivery experience.

• General Skills:

+ Analytical and systems thinking to translate Data Lake project needs into secure, reusable AWS infrastructure patterns. + Strong written and verbal communication skills for working across Cloud Platform, Data engineering, security, architecture, and operations teams. + Problem-solving skills for troubleshooting Terraform, AWS infrastructure, deployment pipelines, permissions, networking, and operational issues. + Collaboration skills to join Data Engineering team projects while representing Cloud Platform standards and operating practices. + Adaptability to work with changing AWS services, Data Lake requirements, infrastructure standards, and AI-assisted development practices. + Initiative and ownership to drive infrastructure tasks from requirements through implementation, review, deployment, and operational handoff. + Continuous learning mindset for Terraform, AWS Data Lake services, platform engineering, DevSecOps, GitHub cloud services, and GitHub Copilot-assisted development methods. + Attention to detail and disciplined review habits to validate GitHub Copilot and other AI-generated code, documentation, and operational recommendations before use. + Ability to balance developer experience, operational excellence, security, and governance when designing reusable platform capabilities.

• Specialized Skills:

+ Required:

• Hands-on Terraform development, including reusable modules, remote state, versioning, automated testing, policy validation, code review, and environment promotion.
• AWS infrastructure services for Data Lake platforms, including IAM, VPC, S3, KMS, CloudWatch, CloudTrail, AWS Config, networking, and guardrails.
• Experience using GitHub Enterprise, GitHub Actions, GitHub Packages, protected branch workflows, automated validation, and Infrastructure-as-Code delivery pipelines.
• Experience using GitHub Copilot and AI-assisted workflows for Terraform development, testing, documentation, troubleshooting, review preparation, and responsible AI-assisted engineering.
• Understanding of DevSecOps practices, including least-privilege IAM, secrets management, policy guardrails, secure pipelines, and operational controls.
• Experience implementing Policy as Code and infrastructure validation using tools such as OPA, Sentinel, Checkov, or equivalent frameworks.

+ Preferred:

• AWS Data Lake services such as S3 data zones, AWS Glue, Lake Formation, Athena, data cataloging, and secure access models.
• Experience with platform engineering concepts such as reusable templates, self-service workflows, golden paths, shared modules, and internal developer enablement.
• Experience applying observability, logging, metrics, tracing, anomaly detection, or AIOps practices to improve operational support.
• Experience with FinOps practices such as tagging standards, budget controls, usage reporting, rightsizing, and cost-aware architecture.
• AWS, Terraform, GitHub, cloud architecture, DevOps, security, data, or generative AI certification is preferred