BRETT WILLEVER

Platform delivery & automation

Reusable landing zones and data contracts get engineers working sooner.

• Built Terraform templates and modules for environment-based project layouts, with separate compute, data, and network projects. Automated service setup using a power user and Terraform service account.
• Built a Firestore-backed data-product management layer for inbound and outbound data contracts, policies, access, and event processing.
• Built IOTA/Hub66 frameworks to standardize data ingestion, transformation, integration, and delivery across client environments.
• Used declarative configuration, CI/CD, reusable modules, and automated checks to make infrastructure deployments more consistent.

Client outcomes & data products

Database migrations and public data platforms built for client teams.

• Applied privacy controls to sensitive relationships between datasets. Redacted data, restricted derived datasets to private use, and turned large datasets into metrics and KPIs.
• Delivered systems across finance and insurance, construction, manufacturing, healthcare and life sciences, retail, SaaS, e-commerce, advertising and marketing, aerospace, and public education.

Architecture, security & governance

Multi-cloud infrastructure with access controls, policy checks, and shared standards.

• Designed and managed multi-cloud environments with reusable infrastructure, policy automation, access controls, and monitoring.
• Designed distributed systems and cloud data platforms for high availability, fault tolerance, analytics, and data processing.
• Applied zero-trust security through identity-based access, least-privilege permissions, encryption, network segmentation, and automated compliance checks.
• Set architecture standards for provisioning, resource management, security, observability, and recovery.

Data, ML & operational reliability

Data pipelines, model operations, monitoring, and automated recovery.

• Added MLOps, ML Reliability Engineering (MLRE), and DevSecOps practices to platform deployments, model lifecycle management, and infrastructure operations.
• Built automated monitoring, policy enforcement, and recovery workflows to reduce manual intervention.
• Built data pipelines and distributed processing for structured and unstructured data, analytics, and machine learning.

Technical leadership

Work with clients and engineers to turn requirements into working systems.

• Brought cloud engineering, cybersecurity, data architecture, and machine learning together in designs that met client requirements.
• Worked with engineering teams and clients to turn requirements into system designs, delivery plans, and production deployments.

Contributions & outcomes

• Reduced platform costs by 35% during the initial six-month monitoring period, representing tens of thousands of dollars in savings.
• Replaced repeated data processing and memory-heavy jobs with event-driven functions and infrastructure that could scale vertically and horizontally.
• Automated insurance-assistance and prior-authorization workflows, reducing manual steps and supporting faster patient treatment.
• Helped the organization start its machine-learning initiative 12–18 months earlier than planned.
• Led a data team working on pipelines that supported continuous learning while keeping costs down.

Contributions & outcomes

• Scaled workloads from hundreds of thousands in lower environments to volumes approaching millions in production.
• Owned deployment templates and methods, coordinated infrastructure changes with cloud teams, and worked with data architects on approvals and expansion.
• Built CI/CD pipelines, reusable data models, and infrastructure as code for a containerized data environment with highly available services.
• Led ModelOp governance for continuous supervised learning and near-real-time log analysis for DevSecOps.

Contributions & outcomes

• Supported hundreds of robots and pharmacy automation systems, including Parata, Deno, and Kalish equipment, pneumatic systems, bottling hoppers, motors, automated weighing systems, and PLC motor/air controllers.
• Added equipment data extraction and embedded streaming pipelines, aggregating telemetry to support software-defined tuning rules and configuration changes throughout the day.
• Helped improve specialty and home-delivery pharmacy throughput, focus preventive maintenance schedules, and reduce downtime.
• Built a serverless SPA backed by Cloud SQL, replacing site-specific spreadsheets for inventory, schedules, routines, and maintenance.
• Made inventory visible across sites so teams could locate and share parts. Provided remote support, site visits, and training at other facilities.