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Job Description
At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams.
Key Responsibilities
- Samsara is seeking a Data Engineer to join our Data team, comprising both Data Scientists, Data Analysts, and Data Engineers. Our team is at the forefront of enhancing data analysis efficiency and effectiveness. Our data engineers develop and maintain data pipelines integral to our analytics data model.
- As a Data Engineer, your primary responsibility will be designing and maintaining data pipelines, primarily utilizing SparkSQL and Pyspark, within our central data lake. These pipelines are crucial for ingesting and transforming source data from our IOT devices and software products into our core data model, facilitating statistical analysis, model training, and dashboard creation.
- This is a remote position open to candidates residing in the US. Relocation assistance will not be provided for this role.
- Build and maintain highly reliable computed tables, incorporating data from various sources, including unstructured data like video and audio, Samsara sensor & product data, and customer metadata.
- Access, manipulate, and integrate external datasets with internal data.
- Deliver high-quality data with strong uptime and reliability requirements, including customer-facing data sets.
- Collaborate closely with cross-functional teams such as Data Science & Analytics, AI/ML, and other Data Engineers to ensure high-quality data for diverse purposes from causal inference, model training, and dashboarding.
- Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.
Requirements
- BA / MS degree in Computer Science, Statistics, or a related discipline.
- 4+ years experience in a data engineering-focused role.
- Demonstrated experience in designing data models at scale.
- Proficiency in building ETL pipelines to handle large volumes of data.
- Experience with Spark-based data platforms.
- Strong command of at least one data orchestration tool (e.g Airflow, Dagster, or Prefect).
- Expertise in SQL, Python, and working with REST APIs.
- Familiarity with software engineering fundamentals and reading backend development code.
- Experience with version control systems such as Git/GitHub.
- Familiarity with time series data and late-arriving data.
- Knowledge of Databricks, Delta Lakes, and Dagster.
- Previous experience working in a public cloud (e.g AWS, GCP, Azure).
- Exposure working on a data model for a product’s first-party data.
- Exposure to complex data, including ML outputs and/or client-side signals.
- The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below.
- Annual Base Salary
- $99,365
- —
- $167,000 USD
Benefits & Perks
- At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time.
- Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here.
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