Senior Data Platform Engineer

About the role

The Integrations, Data Engineering and AI (IDEA) team within Samsara’s Business Technology organization is looking for a Senior Data Platform Engineer to join our team. We enable various teams at Samsara to leverage GenAI and data to glean insights and make data-driven decisions by delivering a reliable data platform and trustworthy data and analytics. We are a team that are passionate about leveraging quality data and AI to deliver a great customer experience. Our team promotes an agile, collaborative, supportive environment where diverse thinking, innovative design, and experimentation is welcomed and encouraged.

This role is open to candidates residing in Canada.

You should apply if:

• You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely.
• You are the architect of your own career: If you put in the work, this role won’t be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development, countless opportunities to experiment and master your craft in a hyper growth environment.
• You’re energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers.
• You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by a high-calibre team that will encourage you to do your best.

In this role, you will:

Databricks

• Administer and monitor Databricks workspaces and underlying AWS Infra: develop platform admin tools and capabilities to effectively administer, monitor, track and troubleshoot various platform resources: (clusters, catalogs, users, groups, databases, storage and security).
• Act as the primary Databricks SME, assisting and guiding teams on platform features and best practices.
• Collaborate with data engineers, analysts, and data scientists to operationalize and optimize workflows and data pipelines.

Infrastructure & DevOps

• Oversee data-engineering dev ecosystem, including dev-tooling, CI/CD pipelines, and monitoring frameworks.
• Own implementation and management of IaaC (Terraform, CloudFormation) and CI/CD automation for Databricks and AWS resources.
• Ensure security, high availability, disaster recovery, and compliance across data services.
• Incorporate DevOps best practices including automated testing, deployment, observability, and monitoring.

Cross-Functional Collaboration & Enablement

• Engage directly with internal cross-functional stakeholders to understand their data needs and design scalable solutions.
• Collaborate with engineers, managers, and vendor representatives in evaluating new features and solutions. Lead rapid prototyping and proof-of-concepts to evaluate for performance, cost, security, scalability, observability.
• Provide mentorship to junior team members, and provide technical guidance, training, and knowledge-sharing across teams.

Minimum requirements for this role:

• Bachelor's or Master's degree in Computer Sciences, Software Engineering, Electrical Engineering, Computer Engineering, or related discipline.
• 10+ years experience in a Software Engineering, Platform Engineering, Data Engineering, DevOps/DataOps or similar technical role, including at least 2+ years experience in data infrastructure or platform focused role.
• Experience building, delivery and administering large-scale production-grade data platforms and services to data engineering, business analyst and data-science teams.
• Solid knowledge of Databricks features and administration, including Unity Catalog, cluster management, security, conducting troubleshooting and root-cause analysis, and performance optimization.
• Experience and familiarity with AWS services and Cloud Infrastructure provisioning, management, monitoring, and security (e.g., S3, IAM, RDS, Lambda, API-Gateway, VPC, EC2, ECS/EKS).
• Strong knowledge of SQL and Python, and hands-on data-engineering experience in designing and developing data pipelines and ETL routines from a variety of sources (SaaS corporate systems, APIs, RDBMS).
• Skilled with change-data capture, incremental and batch loading techniques. Experienced in troubleshooting underlying issues and translating them into technical solutions.
• Excellent problem-solving, communication, and stakeholder management skills.

An ideal candidate also has:

• Experience delivering and managing Databricks and AWS Infra for 100s of users.
• Experience as a technical lead.
• Knowledge of DevOps tools and practices: GitHub/GitLab, CI/CD systems, Terraform, monitoring/logging tools (e.g., Datadog, CloudWatch).
• Experience implementing robust data governance and security measures to ensure data integrity and compliance.