Data Platform Reliability Engineer

D.R. Horton•Arlington, TX

About The Position

D.R. Horton is seeking a Data Platform Reliability Engineer, also described as a Platform Engineer / Data Reliability, to help ensure its modern data foundation is reliable, observable, automated, and ready to support analytics and AI at enterprise scale. The role focuses on engineering monitoring, resilience, performance, deployment, and operational automation, while helping teams detect, prevent, and resolve platform issues. It complements the DevSecOps Engineer, who focuses on the software delivery platform, and the AI Platform Engineer, who focuses on model and agent services. The successful candidate will bring an SRE mindset and strong engineering discipline to building platforms that teams can trust as critical business capabilities. Success means platform teams can define and meet reliability targets, incidents become rarer and shorter, and automation replaces operational toil. The role also involves partnering across the organization, applying practical new capabilities, and identifying opportunities for data, AI, and digital solutions to create business value. Overnight travel is required.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience.
At least 5 years of platform engineering, SRE, DevOps, DataOps, cloud infrastructure, database/platform administration, or related experience.
Strong automation skills using Python, PowerShell, Go, or comparable languages and infrastructure-as-code tools.
Experience with observability, incident management, CI/CD, cloud security, reliability engineering, and production operations.
Working knowledge of modern data platforms and distributed systems.
Demonstrated ability to work independently, take ownership, communicate clearly, and deliver results in an evolving environment.
Ability to build trusted relationships across the organization, balancing enterprise standards with business needs and operating realities.

Nice To Haves

Experience with Snowflake, Azure, Kubernetes, GitHub, Terraform/OpenTofu, Datadog/OpenTelemetry, Kafka or Azure Event Hubs and streaming platforms, Airflow/Dagster-class orchestration, LLM and AI workload observability, or comparable technologies.
Experience in homebuilding, real estate, construction, mortgage, title, land development, sales, purchasing, finance, customer care, or another distributed operating business.
Experience working in a large enterprise with complex enterprise environments.
Experience founding, incubating, or building new products, capabilities, or businesses from the ground up.

Responsibilities

Automate platform provisioning, configuration, deployment, monitoring, health checks, and remediation using code and infrastructure-as-code.
Define and operate SLIs, SLOs, service tiers, alerting, incident response, root-cause analysis, and post-incident improvement practices.
Implement observability across data pipelines, platform services, workloads, APIs, and AI services.
Improve platform security, access, secrets management, resilience, disaster recovery, capacity, and performance.
Partner with engineering teams to embed reliability and operability into new products before production launch.
Represent the function in cross-functional discovery, architecture, governance, operational-readiness, and continuous-improvement activities as appropriate.
Stay current on relevant data, AI, digital, software, and industry practices, applying new capabilities when they create practical business value.
Identify, shape, and pilot opportunities where data, AI, and digital capabilities can create business value, with an owner's mindset and a bias toward building, testing, and learning quickly.
Conduct all business in a professional and ethical manner.
Travel overnight.