Senior Data Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design and manage comprehensive data pipelines and backend ingestion workflows, contributing to the development of Samsara's Data Platform for enhanced automation and analytics.

• Handle data from diverse sources such as ERP (Netsuite), CRM (Salesforce), Product, Order Flow, and Support ticket information.

• Oversee vital data pipelines to support growth strategies and advanced analytical efforts.

• Enable data integration and transformation for seamless data transfer between applications, ensuring compatibility with data layers and the data lake.

• Enhance data architecture, data quality, monitoring, observability, and data availability.

• Construct data transformations using SQL/Python to create data products utilized by Analytics, Marketing Operations, and Sales Operations teams.

• Architect, develop, and manage large-scale Spark and PySpark workflows for both batch and streaming data processing within Databricks and cloud environments.

• Improve Spark job efficiency by fine-tuning partitioning, shuffle, caching, and resource allocation for reliable and efficient production performance.

• Establish and uphold data engineering standards, patterns, and best practices across the team.

• Design systems with long-term sustainability in mind: clear contracts, testable components, and considerate failure modes.

• Partner with platform and infrastructure teams to advance the foundational architecture of Samsara's enterprise data ecosystem.

• Develop and sustain MCP (Model Context Protocol) servers that present Samsara's data assets and engineering workflows to AI models and internal tools.

• Work alongside platform teams to incorporate agentic workflows into the data engineering lifecycle.

• Assess and implement emerging AI-native tools for data engineering, staying ahead of trends on how LLMs and agents can expedite data tasks.

• Advocate for, exemplify, and integrate Samsara's cultural principles as the company scales globally.

• Mentor junior team members and provide technical guidance, training, and knowledge-sharing across teams.

• Engage directly with internal cross-functional stakeholders to ascertain their data requirements and design scalable solutions.

• Lead end-to-end projects, serving as the primary contact for stakeholders.

⛳️ Requirements

• A bachelor's degree in computer science, data engineering, data science, information technology, or a related engineering discipline.

• Over 8 years of professional experience as a Software Engineer with a focus on data or as a Data Engineer.

• More than 5 years of experience in constructing and maintaining large-scale, production-quality end-to-end data pipelines, including Data Modeling.

• At least 5 years of practical experience with Spark/PySpark in a production setting, including job optimization and performance enhancement.

• Strong programming skills in Python and SQL, along with experience in cloud data warehouse/lakehouse technologies (e.g., Snowflake, Google BigQuery, Databricks, or Apache Iceberg).

• Familiarity with ETL tools such as Fivetran, DBT, or similar solutions.

• Experience with API development using Python-based frameworks for data pipeline ingestion.

• Proficient in RDBMS technologies like MySQL, AWS RDS/Aurora, PostgreSQL, Oracle, MS SQL Server, or equivalent.

• Experience with cloud platforms such as AWS, Azure, and/or GCP.

🏝️ Benefits

• Flexible working model

• Professional development stipend

• Comprehensive health and parental leave plans

• Eligibility for RSU grants and ongoing refresh opportunities linked to performance

• Competitive total compensation through a blend of base salary, performance-based bonuses, and equity