Sr. Data Architect, Large Scale Distributed Systems

About Us:

Proofpoint is a global leader in human- and agent-centric cybersecurity. We protect how people, data, and AI agents connect across email, cloud, and collaboration tools. Over 80 of the Fortune 100, 10,000 large enterprises, and millions of smaller organizations trust Proofpoint to stop threats, prevent data loss, and build resilience across their people and AI workflows. Our mission is simple: safeguard the digital world and empower people to work securely and confidently. Join us in our pursuit to defend data and protect people.
How We Work:

At Proofpoint you’ll be part of a global team that breaks barriers to redefine cybersecurity guided by our BRAVE core values:

Bold in how we dream and innovate

Responsive to feedback, challenges and opportunities

Accountable for results and best in class outcomes

Visionary in future focused problem-solving

Exceptional in execution and impact
Role Overview

We are seeking an experienced Senior Architect to lead the design and evolution of enterprise-scale distributed systems supporting 50M+ connected sensors and high-volume event processing pipelines .

This role is critical to building and operating mission-critical backend platforms that process millions of events per second across both synchronous and asynchronous architectures , with stringent requirements for scalability, reliability, security, and performance .

The ideal candidate brings a proven track record of architecting and scaling production-grade systems at extreme scale , along with the ability to drive technical strategy, governance, and cross-functional alignment in a complex enterprise environment.
Key Responsibilities
Architecture & System Design

- Define and lead the architecture of large-scale distributed systems capable of ingesting and processing high-velocity data streams from 50M+ sensors

- Design resilient systems across synchronous (API-driven) and asynchronous (event-driven, streaming) paradigms

- Establish architectural standards for scalability, fault tolerance, and performance optimization

Data Platform Engineering

- Architect real-time and batch data pipelines for high-throughput ingestion, transformation, and storage

- Drive design decisions across streaming, processing, and storage layers to ensure optimal performance and cost efficiency

- Enable support for time-series, event-driven, and analytical workloads

Technology Strategy & Governance

- Define and enforce enterprise architecture principles, standards, and best practices

- Evaluate and guide adoption of modern data technologies, including:
- Distributed messaging systems (e.g., Kafka, Pulsar)

- Scalable data stores (e.g., Cassandra, DynamoDB, Bigtable, ClickHouse, Elasticsearch)

- Stream and batch processing frameworks (e.g., Flink, Spark, Beam)

- Ensure alignment with security, compliance, and data governance requirements

Scalability, Reliability & Observability

- Establish and operationalize SLAs, SLOs, and error budgets

- Design for high availability, multi-region resilience, and disaster recovery

- Implement enterprise-grade observability frameworks (monitoring, logging, tracing)

Leadership & Collaboration

- Partner with engineering, product, security, and data teams to align architecture with organizational objectives

- Provide technical leadership, mentorship, and architectural oversight across multiple teams

- Lead design reviews and ensure adherence to architectural standards

Required Qualifications

Experience

- 10+ years of experience in distributed systems and backend architecture

- Demonstrated success in scaling systems to:
-
50M+ connected devices/sensors , or

- Comparable high-scale environments (e.g., IoT, telecom, fintech, ad-tech, infrastructure platforms)

- Proven experience with high-throughput event-driven architectures in production environments

Technical Expertise

- Deep understanding of distributed systems concepts, including:
- CAP theorem, consist