Senior Platform Engineer, Data & AI Infrastructure

Purpose We're looking for a DevOps / Cloud Security / Data Infrastructure Engineer who will build, operate, and evolve the cloud infrastructure and data platform that powers McKinney's internal AI and analytics products. You'll own the foundation that enables our data lakehouse — managing pipelines, orchestration, infrastructure-as-code, and platform reliability so that our engineering and data teams can ship fast and with confidence. You'll work alongside our Applied Emerging Technology (AET) department to operate a modern stack built on AWS, Snowflake, Fivetran, DBT, FastAPI, and Okta (auth0). You'll be hands-on with infrastructure automation, CI/CD, observability, and data pipeline health — from early design through deployment, monitoring, and iteration. Ideal Candidate You think in systems: pipelines, infrastructure state, observability, and failure modes are your natural vocabulary. You're comfortable owning cloud infrastructure end-to-end, from provisioning to incident response. You have a strong data engineering sensibility. You understand ELT patterns, warehouse architecture, and what makes pipelines reliable and cost-efficient. You automate everything, write infrastructure as code, and treat configuration drift as a bug. You collaborate closely with software engineers, data analysts, and product owners. You're curious about AI infrastructure and excited to support LLM-powered products in production. You have used and are learning to leverage AI-coding assistants ( codex, claude-code, etc. ) Networking / cloud security experience Responsibilities Design, build, and maintain cloud infrastructure on AWS using Terraform and GitOps (or comparable) workflows; manage environments (dev, staging, production) with consistency and auditability. Own and operate Snowflake data warehouse infrastructure: virtual warehouse sizing and cost governance, resource monitors, account-level configurations, and integration with Fivetran and/or DBT. Manage and monitor ELT connectors; troubleshoot sync failures, schema drift, and performance issues; coordinate with source system owners on connector changes. Support and extend pipelines: manage job scheduling, run monitoring, model dependencies, and test coverage; work with data practitioners on performance optimization. Operate and harden our dev platform: manage user access, environment variables, secrets, deployment configurations, and platform upgrades. Administer Okta SSO integrations and auth0 across the platform; manage application assignments, SCIM provisioning, and authentication policies. Build and maintain CI/CD pipelines for infrastructure and application code; enforce automated testing, security scanning, and deployment gates. Author and maintain Dockerfiles and container images; manage image lifecycle in a container registry; enforce container security best practices. Establish and maintain observability across the stack: metrics, logs, traces, and alerting for pipelines, APIs, and platform services. Manage secrets, IAM roles, and least-privilege access policies across AWS services; maintain a strong security and compliance posture. Perform capacity planning, cost optimization, and FinOps hygiene across AWS and Snowflake; report on platform spend and efficiency. Document infrastructure architecture, runbooks, and incident postmortems; contribute to disaster recovery and business continuity planning. Qualifications Professional Skills AWS: Strong hands-on experience with core services (EC2, ECS/Fargate, Lambda, RDS, S3, IAM, VPC, CloudWatch, Secrets Manager, ECR, CodeBuild/CodePipeline); experience with cost optimization and tagging strategies. Infrastructure as Code: Terraform (required); GitOps or comparable workflows; experience managing multi-environment infrastructure with state management and module reuse. Snowflake Administration: Virtual warehouse management, resource monitors, role-based access control, data sharing, and cost governance; familiarity with Snowflake architec…