GCP Distributed Systems Architect
Primary stack
Nice to have's
Job description
About the Position
We are searching for a GCP Distributed Systems Architect with strong expertise in Software Engineering and Solutioning, Kubernetes, Machine Learning, Data & Analytics, and large-scale distributed systems. This is a highly technical, hands-on architecture position centered on solution design, technical leadership, code reviews, pattern design, sharing best practices, and proof-of-concept work, rather than day-to-day feature delivery or ML/Ops operations.
Responsibilities
- Establish and evaluate the architecture of large-scale distributed systems running on Google Cloud Platform (GCP)
- Deliver technical leadership for solutions built on Apache Beam and Kubernetes
- Assess code and implementation approaches to uphold best practices, scalability, maintainability, and performance
- Build proof-of-concepts, reference implementations, and sample code to demonstrate and validate architectural and engineering patterns
- Advise engineering teams on system design, distributed processing patterns, and domain-driven architecture
- Offer guidance on application structure, service boundaries, scalability, resilience, and operational preparedness
- Contribute to architectural decisions for highly scaled environments, including platforms running with 10,000 or more pods
- Work alongside engineering teams as a hands-on technical authority without taking on day-to-day DevOps responsibilities
Requirements
- No less than 8 years of applied professional experience
- At least 3 years in Lead, Manager, Owner, Architect, or Coordinator positions
- Minimum of 2 years leading a team of at least 20 members
- Involvement in 5 or more full-cycle projects, or contribution across multiple projects spanning various phases of the development lifecycle
- Practical experience with Kubeflow pipelines for Directed Acyclic Graphs (DAGs) and BigQuery for large-scale data workloads
- Advanced command of Kubernetes for orchestrating containerized workloads at scale
- Solid background in architecting and steering complex distributed systems
- Track record of working within highly scaled environments, including platforms operating with 10,000 or more pods
- Deep familiarity with Domain-Driven Design and contemporary software architecture principles
- Strong hands-on ability to develop proof-of-concepts and sample code
- Demonstrated experience carrying out architecture reviews and code reviews with a focus on best practices
- Extensive expertise across GCP and commonly used cloud architecture patterns
- Capacity to mentor and influence senior engineering teams
- Confident English communication skills at B2 level or above, with the ability to explain technical topics clearly to a range of audiences
Nice to Have
- Practical exposure to key GCP services including GKE, Pub/Sub, Cloud Storage, and IAM
- Hands-on background with Apache Beam for constructing data processing pipelines
- Experience shaping engineering standards and defining architectural guardrails
- Involvement in platform modernization projects or large-scale data processing systems
- Awareness of event-driven architecture and streaming platforms
- Previous engagement in advisory, staff, principal, or architect-level positions
- Working knowledge of Google Cloud Dataflow for creating and running scalable data pipelines
- Hands-on software development experience using Python
- Familiarity with Apache Airflow, together with clean code habits, code review culture, engineering fundamentals, machine learning workflows, and broader software engineering practices
About the Company
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