Key skills
PythonSQLAIMLETLData EngineeringAnalyticsDatabricksSparkAirflowAWSAzureGCPGitGitHubVersion ControlCustomer Success
About this role
Samsara is the pioneer of the Connected Operations™ Cloud, which enables organizations to harness IoT data for actionable insights. The Senior Data Engineer will design and maintain data pipelines that are essential for transforming and analyzing data from IoT devices and software products.
Responsibilities:
- 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