DevOps Engineer, Data Platform

at  Grammarly

Grammarly is excited to offer a remote-first hybrid working model. Grammarly team members in this role must be based in the United States and, depending on business needs, they must meet in person for collaboration weeks, traveling if necessary to the hub(s) where their team is based.
This flexible approach gives team members the best of both worlds: plenty of focus time along with in-person collaboration that fosters trust and unlocks creativity.

THE OPPORTUNITY

To achieve our ambitious goals, we’re looking for a Software Engineer to join our Data Platform team and help us build a world-class data platform. Grammarly’s success depends on its ability to efficiently ingest over 60 billion daily events while using our systems to improve our product. This role is a unique opportunity to experience all aspects of building complex software systems: contributing to the strategy, defining the architecture, and building and shipping to production.
Grammarly’s engineers and researchers have the freedom to innovate and uncover breakthroughs—and, in turn, influence our product roadmap. The complexity of our technical challenges is growing rapidly as we scale our interfaces, algorithms, and infrastructure. You can hear more from our team on our technical blog.
As a Senior DevOps Engineer on the Data Platform team, you will lead cloud infrastructure design, automation, and management, focusing on Databricks and AWS, ensuring the platform is scalable, secure, and cost-effective. You will be critical in optimizing data processing and machine learning workflows, guaranteeing high performance and uptime for critical systems. Your expertise in Databricks and AWS infrastructure and a focus on cost management will be vital to driving platform efficiency.

You will work closely with data engineers, ML teams, and infrastructure engineers to automate and optimize workflows, manage infrastructure, and ensure the platform supports real-time analytics and machine learning at scale.

• Design, implement, and manage scalable infrastructure focusing on Databricks, AWS, and Spark clusters to support data pipelines and lakes.
• Build and optimize CI/CD pipelines for deploying and managing Databricks clusters, data pipelines, and real-time data workflows.
• Use tools like Terraform, Kubernetes, and Ansible to orchestrate and automate infrastructure tasks, including provisioning, scaling, and monitoring.
• Implement and manage monitoring and logging systems to ensure data infrastructure’s high availability, security, and performance, focusing on Databricks and AWS environments.
• Implement cloud security best practices, manage access control and encryption, and ensure the platform complies with data privacy regulations to ensure security and compliance.
• Collaborate with cross-functional teams to maintain cost management strategies, optimizing resource utilization across Databricks, AWS, and other data infrastructure components.

QUALIFICATIONS

• Has 5+ years of experience in DevOps with expertise in managing AWS infrastructure and Databricks environments.
• Has strong experience with Spark clusters, data lakes, and managing large-scale data pipelines in a cloud environment.
• Is skilled in orchestration, monitoring, and logging, using tools like Terraform, Kubernetes, and Airflow for managing cloud resources and data workflows.
• Understands security and compliance best practices, ensuring data infrastructure is secure, compliant, and aligned with privacy regulations.
• Has experience with cost management and optimization of cloud resources, with a focus on AWS and Databricks.
• Is a problem solver who enjoys building scalable, automated solutions that improve platform reliability and efficiency.
• Embodies our EAGER values—is ethical, adaptable, gritty, empathetic, and remarkable.
• Is inspired by our MOVE principles: move fast and learn faster; obsess about creating customer value; value impact over activity; and embrace healthy disagreement rooted in trust.
• Is able to meet in person for their team’s scheduled collaboration weeks, traveling if necessary to the hub where their team is based.

Please refer the Job description for details