Senior Cloud Platform Engineer

Senior Cloud Platform Engineer

This is a senior engineering opportunity for a cloud infrastructure specialist who wants to shape reliable, scalable, and secure data platforms. You will play a key role in designing and evolving cloud infrastructure on Google Cloud Platform (GCP) while enabling data and machine learning teams to move faster. The role combines infrastructure architecture, Infrastructure-as-Code, CI/CD, security, platform operations, and internal developer tooling. You will work closely with distributed engineering teams across multiple regions and collaborate directly with technical and business stakeholders. You will have significant ownership over outcomes, with the freedom to improve processes, platform capabilities, and engineering practices. The environment values technical excellence, knowledge sharing, thoughtful use of AI-assisted engineering, and continuous improvement.

Accountabilities:

• Design and architect scalable, secure, and resilient cloud infrastructure, developing Infrastructure-as-Code solutions with Terraform and driving standardization initiatives.
• Build, optimize, and maintain CI/CD pipelines for infrastructure deployment, promoting DevOps and DevSecOps best practices.
• Operate and continuously improve GCP data platform services, including BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub, in close collaboration with data and ML engineering teams.
• Design and manage cloud IAM and service accounts while enforcing least-privilege access and strong security practices.
• Lead incident response, troubleshooting, and root cause analysis for platform issues, implementing improvements that reduce recurring incidents.
• Participate in an on-call rotation as the platform's operational coverage evolves.
• Contribute to the development and maintenance of an Internal Developer Platform, including software catalog entries, scaffolder templates, and accurate technical documentation.
• Partner with data and ML engineering teams to onboard services and pipelines into the platform catalog, ensuring ownership and metadata are correctly represented.
• Use AI-assisted engineering tools such as Claude Code to support infrastructure development, code reviews, documentation, and day-to-day engineering workflows.
• Share effective AI engineering practices and prompting approaches with colleagues while promoting thoughtful, secure, and responsible use of AI.
• Work with finance, compliance, BI, data science, and other stakeholders to understand business needs, evaluate trade-offs, and translate requirements into effective platform solutions.
• Contribute to technical standards, runbooks, documentation, and engineering practices that improve the reliability and usability of the platform.
• Take ownership of initiatives from design through delivery, proactively identifying opportunities to improve platform performance, security, reliability, and developer experience.

Requirements

• 8+ years of experience in cloud infrastructure engineering, with substantial hands-on experience designing and administering complex GCP environments.
• Strong production-scale experience with Google Cloud services including BigQuery, Dataflow, Dataproc, Cloud Storage, and Pub/Sub.
• Strong understanding of GCP networking and cloud architecture, including VPC, VPC Service Controls (VPC-SC), connectivity solutions, and IaaS/PaaS architectural patterns.
• Extensive hands-on experience with Terraform and multi-environment configuration management across cloud platforms.
• Strong experience building and maintaining GitLab CI/CD pipelines, runners, and merge request workflows.
• Solid understanding of cloud IAM, access control, least-privilege principles, and security best practices.
• Experience working as a platform engineering partner to data or ML teams, with a focus on building infrastructure that is reliable, accessible, and genuinely usable.
• Strong consultative and stakeholder-management skills, with the ability to understand business requirements, challenge assumptions constructively, and communicate technical trade-offs without unnecessary jargon.
• Strong analytical and problem-solving abilities, particularly when diagnosing complex infrastructure and platform issues.
• Excellent communication and collaboration skills, with experience working effectively across distributed and international teams.
• AWS experience is an advantage.
• Experience with Backstage, including software catalog configuration, scaffolder templates, or plugin development, is desirable.
• Familiarity with data platform concepts such as medallion architecture, lakehouse patterns, Airflow, or dbt is a plus.
• Experience managing Databricks environments is advantageous.
• Practical professional experience using AI coding assistants such as Claude Code, GitHub Copilot, Cursor, or similar tools is a plus.
• Experience within regulated financial services environments is beneficial.

Benefits

• Flexible working hours and work-from-home opportunities.
• Performance-related bonus opportunities.
• Insurance and medical plans.
• Career-focused technical and leadership development programs.
• Mentoring opportunities with experienced leaders and opportunities for career progression.
• Unlimited access to LinkedIn Learning and other professional development resources.
• Opportunities to expand your professional network through committees, sports, and social clubs.
• Matched giving for fundraising activities.
• Contribution toward gym memberships and wellness initiatives.
• Free lunch, snacks, and fruit.
• A day off on your birthday.
• Two days of paid volunteering leave per year.
• Additional salary, leave, healthcare, and employee benefits may apply according to the partner company's employment policies.