Senior Cloud-Native Distributed Systems Architect

Jobtailor; California (MO); On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor is seeking a senior engineering leader to architect and scale cloud-native distributed services and data platforms. You will drive real-time analytics capabilities and federated data services, delivering customer-facing offerings that integrate across multiple teams.

The role requires 15+ years of leadership in large-scale systems, deep cloud experience (AWS/GCP/Azure), and hands-on design skills.

Qualifications

• 15+ years of engineering and architectural leadership.
• Bachelor’s, Master’s, or PhD in CS/engineering preferred.
• Strong foundations in large-scale data engineering and federated datasets.
• Experience designing distributed query engines and low-latency analytics.
• Deep knowledge of cloud-native architecture across AWS/GCP/Azure; hybrid environments.
• Hands-on coding in system design; AI-assisted tools.
• Proven ability to communicate roadmaps to executives and stakeholders.
• Experience with Spark, Kafka, Parquet, Go, Java.
• Senior leadership experience (Principal/ Distinguished Engineer).
• Strategic thinker translating vision into executable roadmaps.
• Strong communicator to technical and non-technical audiences.
• Ownership mindset across multiple teams.

Responsibilities

• Architect, design, and scale large cloud‑native distributed services and data platforms.
• Design and build federated distributed query engines and data services for real-time analytics.
• Lead development of customer-facing services on top of the platform.
• Provide hands‑on technical leadership: prototype, validate, and implement solutions using AI-assisted tools.
• Define architectures and roadmaps; influence executives and product stakeholders.
• Mentor and coach engineering teams; raise standards and develop leaders.
• Collaborate with product, customer engineering, and support for reliability and UX.
• Guide technology choices and participate in cross‑organization design reviews.

Skills

Strong communication

Mentoring

Strategic thinking

Cross-functional collaboration

Influencing stakeholders

Education

Bachelor’s Degree

Master’s Degree

PhD

Tools

Spark

Kafka

Parquet

Go

Java

AWS

GCP

Azure

Microservices

Job description

• Architect, design, and scale large cloud‑native distributed services and data platforms
• Design and build federated distributed query engines and data services to enable real‑time analytics, dashboards, and ML consumers.
• Lead the development of customer‑facing services that run on top of the platform (integration, data sharing, observability/analytics services), enabling cross‑service capabilities.
• Deliver hands‑on technical leadership: prototype, prototype‑validate , and implement solutions using modern development practices and tools, including AI‑assisted coding workflows.
• Define organization‑wide architectures, methodologies, and roadmaps across multiple teams and products; communicate strategy and influence executive and product stakeholders.
• Mentor and coach engineering teams, raise architectural and operational standards, and help select and develop future technical leaders.
• Collaborate with product, customer engineering, and support teams to ensure reliability, performance, and great user experience for customer‑facing services.
• Contribute to selection of technologies and frameworks, participate in design reviews, and guide cross‑organization implementation choices.

Requirements

• Proficient with AI-First spec driven rapid innovation converting ideas to working prototypes using the AI coding tools.
• Typically, 15+ years of experience in engineering and architectural leadership, designing, building, and operating large distributed systems and cloud platform services.
• Bachelor’s, Master’s, or PhD in computer science, engineering, information systems, or a related quantitative discipline preferred.
• Strong foundations in large‑scale data engineering (OLAP, distributed storage systems, open data formats) and experience with federated datasets.
• Experience designing and optimizing distributed query engines and low‑latency analytics systems.
• Deep knowledge of cloud‑native architecture and microservices at scale across public cloud environments (AWS/GCP/Azure) and hybrid scenarios.
• Hands‑on coding experience in system design and architecture phases; comfort using modern development and AI‑assisted tools.
• Proven ability to create and communicate technical roadmaps and to influence cross‑functional and executive stakeholders.
• Experience with Spark, Kafka, Parquet, Go, Java.
• Large analytics engines or managed analytics services ( BigQuery or equivalent)
• Demonstrated experience operating at senior technical leadership levels (Principal, Distinguished Engineer, or equivalent), with a history of cross‑organization technical impact.
• Strategic thinker who can translate long‑term vision into executable technical roadmaps.
• Strong communicator able to present complex technical concepts to executive and non‑technical audiences.
• Comfortable taking broad ownership and driving projects that touch multiple teams and business units.

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Hard Skills

• Distributed Query Engines
• Low-Latency Analytics Systems
• OLAP
• Spark
• Kafka
• Parquet
• Go
• Java
• Cloud Platforms (AWS/GCP/Azure)
• Microservices

Soft Skills

• Strong Communication
• Mentoring
• Strategic Thinking
• Collaboration
• Influencing Stakeholders

Certifications & Qualifications

• Bachelor’s Degree
• Master’s Degree
• PhD in Computer Science or Related Discipline