Job Description
A Data Engineer at Samsara is responsible for developing and maintaining large-scale data pipelines, integrating diverse data sources, and enhancing the company's data architecture to enable advanced analytics and automation, supporting the company's mission to improve physical operations across various industries.
Key Responsibilities
- Develop and maintain end-to-end data pipelines and backend ingestion processes.
- Build and enhance Samsara's Data Platform to support automation and analytics.
- Manage critical data pipelines to support growth initiatives and advanced analytics.
- Facilitate data integration and transformation between applications to ensure interoperability.
- Improve data architecture, quality, monitoring, observability, and data availability.
- Write data transformations using SQL and Python to generate data products for various teams.
Requirements
- A Bachelor’s degree in computer science, data engineering, data science, information technology, or equivalent engineering program.
- 8 years of work experience as a Data Engineer.
- 3 years of experience in building and maintaining large-scale production-grade end-to-end data pipelines, including Data Modeling.
- Experience with modern cloud-based data-lake and data-warehousing technology stacks, and familiarity with typical data-engineering tools, ETL/ELT processes, and data-warehousing best practices.
- Experience leading end-to-end projects, including being the central point of contact to stakeholders.
- Provide mentorship to junior team members, and provide technical guidance, training, and knowledge-sharing across teams.
- Engage directly with internal cross-functional stakeholders to understand their data needs and design scalable solutions.
- At least 3 years of experience in Python and SQL.
- Exposure to ETL tools such as Fivetran, DBT, or equivalent.
- Experience with Python-based API frameworks for data pipelines.
- Experience working with RDBMS such as MySQL, AWS RDS Aurora MySQL, PostgreSQL, Oracle, or MS SQL-Server.
- Experience with cloud platforms including AWS, Azure, and/or GCP.
- Experience with data warehouses such as Databricks, Google BigQuery, AWS Redshift, Snowflake, or equivalent.
- Comfortable working with business customers to gather requirements and gain a deep understanding of varied datasets.
- Familiarity working with Spark, PySpark, and Terraform.
- Good communication skills and project management skills to relay findings and solutions across technical and non-technical audiences.
- Experience with logging and monitoring tools such as Splunk, DataDog, AWS CloudWatch, or equivalent.
- Experience with AWS Serverless services including API Gateway, Lambda, S3, SNS, SQS, and SecretsManager.
- Ability to perform as a self-starter, responsible, innovative, and technology-driven, performing well both solo and as part of a team.
Benefits & Perks
Competitive total compensation package
Employee-led remote and flexible working
Health benefits
Inclusive work environment with accommodations for persons with disabilities
Flexible working model (in-person, hybrid, or fully remote)
Ready to Apply?
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