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Salary: CAD 110,500 - 143,000 / annual
Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud, a platform enabling organizations to harness Internet of Things (IoT) data to develop actionable insights and improve operations. The company helps digitally transform industries representing over 40% of global GDP, including agriculture, construction, field services, transportation, and manufacturing.
You will join the Data team as a Data Engineer, working alongside Data Scientists, Data Analysts, and other Data Engineers at the forefront of enhancing data analysis efficiency and effectiveness. Your primary responsibility will be designing and maintaining data pipelines, primarily utilizing SparkSQL and PySpark, within the central data lake. These pipelines are crucial for ingesting and transforming source data from IoT devices and software products into the core data model, facilitating statistical analysis, model training, and dashboard creation.
Key responsibilities include:
- Build and maintain highly reliable computed tables, incorporating data from various sources including unstructured data (video and audio), Samsara sensor and 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 datasets
- 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 and embed Samsara's cultural principles as the company scales globally
This is a fully remote position open to candidates residing in Canada. Relocation assistance will not be provided.
REQUIREMENTS:
Minimum requirements:
- BA/MS degree in Computer Science, Statistics, or a related discipline
- 4+ years of 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
Ideal candidate also has:
- Familiarity with time series data and late-arriving data
- Knowledge of Databricks, Delta Lakes, and Dagster
- Previous experience working in a public cloud (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
