Job Description
A Data Engineer at Samsara is responsible for developing and maintaining large-scale data pipelines, managing data integration and transformation, and supporting analytics and automation efforts to enable data-driven decision-making 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, data quality, monitoring, 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, MS SQL-Server, or equivalent.
- 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 work both independently and as part of a team, demonstrating responsibility, innovation, and motivation.
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 including in-person, hybrid, and remote options
Ready to Apply?
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