Job description

About Us At Versa Networks, we're revolutionizing the way businesses connect, secure, and optimize their networks. Our mission is to secure anywhere, anytime access to anything. As a leader in Secure SD-WAN, SSE (Secure Service Edge), SASE (Secure Access Service Edge) and Next-generation Managed Services, we are empowering organizations across the globe to transform their IT infrastructure for the modern cloud era. Our innovative products enable enterprises to deliver a seamless, scalable, and secure digital experience, no matter where their users, devices, or applications are located. Founded by industry veterans and backed by premier venture capital firms, Versa is a market leader driving innovation and growth as it positions itself for a future IPO. We believe in fostering a culture of innovation, collaboration, and customer success. Our team is comprised of passionate, forward-thinking professionals dedicated to driving the future of networking technology. We encourage creativity, offer opportunities for growth, and provide a dynamic environment where our people can thrive and make an impact. At Versa Networks, we don’t just build products – we build relationships, elevate businesses, and shape the digital future. Join us and be part of a fast-paced, cutting-edge company that's making a real difference in how the world connects and communicates. Job Summary We’re seeking a highly skilled Data Engineer to design, build, and maintain production-grade data pipelines that process and transform terabytes of data. In this role, you’ll collaborate closely with data scientists and other SWEs to ensure that our data infrastructure is scalable, reliable, and cost-effective. Responsibilities • Pipeline Development & Deployment: • Architect, develop, and deploy batch and streaming pipelines using Airflow and containerized workflows for cyber-security use-cases. • Containerize data-processing jobs with Docker, orchestrate with Kubernetes, and manage releases with Helm charts. • Distributed Computing: • Build high-throughput data transformations using Dask or Apache Spark. • Maintain training data clusters across hybrid (on-prem and cloud environments). • Optimize training jobs for performance, resiliency, and cost. • Monitoring & Reliability: • Implement observability (logging, metrics, alerting) to maintain pipeline health and SLA adherence. • Troubleshoot, debug, and resolve data-processing failures in production. • Collaboration & Best Practices: • Work with cross-functional teams to define data contracts, schemas, and quality checks. • Enforce software engineering best practices: CI/CD, code reviews, automated testing, and documentation. • Data Modeling & Storage: • Design and maintain data models and schemas for AI/ML continuous training use cases. • Load data into cloud storage and lakes, ensuring performance and accessibility. Qualifications • 3–5 years of professional experience designing and operating production data pipelines at scale. • Containerization & Orchestration: Expertise with Docker, Kubernetes, and Helm. • Workflow Management: Hands-on experience building DAG-based pipelines in Apache Airflow. • Programming: Strong proficiency in Python for data engineering tasks. • Distributed Frameworks: Practical experience with Dask or Apache Spark for large-scale data processing. • Cloud Fundamentals: Familiarity with deploying and managing services in a cloud environment. • Compiled Languages: Experience writing data services in Go or Rust. • GCP Proficiency: Hands-on with Google Cloud services (e.g., Pub/Sub, Big Query, Cloud Storage, GKE). Equivalent experience in other public cloud providers is fine. • ML Pipelines: Exposure to deploying cross-cluster model-training workflows using Ray or similar frameworks. • Infrastructure as Code: Familiarity with Terraform for deployment. • Security & Compliance: Knowledge of data governance, encryption, and role-based access control. Location: United States *Applicants must be authorized to work in the US The pay range for this position at commencement of employment in California, Washington, or New York City is expected in the range of $150,000 to $220,000. A candidate’s specific pay within this range will depend on a variety of factors, including job-related skills, training, location, experience, relevant education, certifications, and other business and organizational needs. Why Versa? At Versa Networks, we believe in taking care of our people – both professionally and personally. We offer a comprehensive benefits package designed to support the well-being, growth, and work-life balance of our employees. When you join our team, you can expect: • Competitive Salary & Incentives: We offer a competitive compensation package with and pre-IPO equity to reward your hard work and dedication. • Health & Wellness: Comprehensive medical, dental, and vision insurance plans to ensure you and your family stay healthy and covered. • Paid Time Off (PTO): Enjoy a generous PTO policy that includes vacation days, sick leave, and paid holidays to recharge and take care of personal matters. • Flexible Work Environment: We understand the importance of work-life balance. Enjoy the flexibility of remote work, and hybrid option to create the work schedule that works best for you. • Professional Development: We believe in continuous learning. Access to training, certifications, and educational resources to help you grow in your career and stay ahead of industry trends. • Employee Recognition: We celebrate achievements both big and small, with regular recognition programs and awards that highlight your contributions to our collective success. • Collaborative Culture: Be part of a dynamic, inclusive, and supportive team where innovation and collaboration are at the heart of everything we do. • Parental Leave: Generous parental leave policies to support you during life's important moments. At Versa Networks, our benefits are designed to help you thrive both inside and outside the office. Join us and experience a rewarding, fulfilling career in a supportive environment that values your health, happiness, and success. Versa Networks is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Requirements

Must-haves

Architect, develop, and deploy batch and streaming pipelines using Airflow and containerized workflows for cyber-security use-cases.
Containerize data-processing jobs with Docker, orchestrate with Kubernetes, and manage releases with Helm charts.
Build high-throughput data transformations using Dask or Apache Spark.
Maintain training data clusters across hybrid (on-prem and cloud environments).
Optimize training jobs for performance, resiliency, and cost.
Implement observability (logging, metrics, alerting) to maintain pipeline health and SLA adherence.
Troubleshoot, debug, and resolve data-processing failures in production.
Work with cross-functional teams to define data contracts, schemas, and quality checks.
Enforce software engineering best practices: CI/CD, code reviews, automated testing, and documentation.
Design and maintain data models and schemas for AI/ML continuous training use cases.
Load data into cloud storage and lakes, ensuring performance and accessibility.
3–5 years of professional experience designing and operating production data pipelines at scale.
Containerization & Orchestration: Expertise with Docker, Kubernetes, and Helm.
Workflow Management: Hands-on experience building DAG-based pipelines in Apache Airflow.
Programming: Strong proficiency in Python for data engineering tasks.
Distributed Frameworks: Practical experience with Dask or Apache Spark for large-scale data processing.
Cloud Fundamentals: Familiarity with deploying and managing services in a cloud environment.
Compiled Languages: Experience writing data services in Go or Rust.
GCP Proficiency: Hands-on with Google Cloud services (e.g., Pub/Sub, Big Query, Cloud Storage, GKE). Equivalent experience in other public cloud providers is fine.
ML Pipelines: Exposure to deploying cross-cluster model-training workflows using Ray or similar frameworks.
Infrastructure as Code: Familiarity with Terraform for deployment.
Security & Compliance: Knowledge of data governance, encryption, and role-based access control.
Location: United States
Applicants must be authorized to work in the US

Nice-to-haves

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Application prep

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Keywords to mirror

dockerkubernetesci/cdaimlaccessibilitypythongorustgcp

Platform: workable
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Paid Time Off

Parental Leave

Wellness

Professional Development