Platform Engineer (Finance)
Platform Engineering at Equifax is a discipline that combines software and systems engineering for building and running large-scale, distributed, fault-tolerant systems. A Platform Engineer ensures that internal and external services meet or exceed reliability and performance expectations while adhering to Equifax engineering principles.
We approach platform engineering as an engineering discipline focused on solving operational challenges through innovative solutions. Our team is responsible for the overall operation of our systems, utilizing a diverse set of tools and methodologies to address a wide range of problems. Key practices include optimizing time spent on operational work, conducting blameless postmortems, and proactively identifying and preventing potential outages.
Our success is rooted in a culture that champions diversity, intellectual curiosity, collaborative problem-solving, and openness. Equifax fosters an environment where individuals from varied backgrounds, experiences, and perspectives come together to collaborate, think boldly, and take calculated risks in a blame-free setting. We empower self-direction on meaningful projects while providing robust support and mentorship to facilitate learning, growth, and a sense of pride in our collective work.
What you'll do
- Manage and optimize system uptime across cloud-native (AWS, GCP) and hybrid architectures.
- Develop Infrastructure as Code (IaC) patterns using technologies such as Terraform, cloud CLI scripting, and cloud SDK programming, ensuring adherence to security and engineering standards.
- Build and optimize CI/CD pipelines leveraging both platform tools (e.g., Jenkins) and cloud-native toolchains (e.g., GitHub Actions) for application build, test, and deployment, as well as cloud architecture patterns.
- Develop automated tooling for various operational workflows, including service request fulfillment to streamline changes into production.
- Design and implement data pipelines and processing solutions within BigQuery to derive operational insights, analyze logs, and monitor critical platform metrics.
- Explore and implement MLOps practices to integrate machine learning models, particularly those leveraging Vertex AI, into production environments, ensuring their reliability, scalability, and robust monitoring.
- Create comprehensive and detailed runbooks for managing, detecting, remediating, and restoring services.
- Troubleshoot and triage complex distributed architecture service maps.
- Participate in on-call rotations for high-severity application incidents, continuously improving runbooks to enhance Mean Time To Recovery (MTTR).
- Lead availability blameless postmortems and drive actionable remediation plans to prevent recurrences.
What experience you need
- Bachelor's degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics), or equivalent practical job experience.
- 5+ years of experience in a combination of software engineering, systems administration, database administration, and networking.
- 2+ years of experience developing and/or administering software in public cloud environments (AWS, GCP).
- Proven experience in monitoring infrastructure and application uptime and availability to ensure functional and performance objectives are met.
- Proficiency in programming and scripting languages such as Python, Bash, Java, Go, JavaScript, and/or Node.js.
- Demonstrable cross-functional knowledge across systems, storage, networking, security, and databases.
- Strong system administration skills, including automation and orchestration of Linux/Windows environments using tools like Terraform, Chef, Ansible, and/or containers (Docker, Kubernetes, etc.).
- Proficiency with continuous integration and continuous delivery tooling and practices, including experience with GitHub Actions.
What could set you apart
- Cloud Certification (AWS, GCP, or other relevant certifications).
- Direct experience working with Jenkins, GitHub Actions, and Argo.
- Hands-on experience with BigQuery, Cloud Composer, or Vertex AI.
- Demonstrable experience implementing MLOps best practices in a professional setting.
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