• Develop and maintain end-to-end data pipelines and backend ingestion workflows, and participate in the build of Samsara's Data Platform to enable advanced automation and analytics. • Work with data from a variety of sources including ERP(Netsuite), CRM(Salesforce), Product, Order Flow, and Support ticket data. • Manage critical data pipelines to enable growth initiatives and advanced analytics. • Facilitate data integration and transformation for moving data between applications, ensuring interoperability with data layers and the data lake. • Develop and improve data architecture, data quality, monitoring, observability, and data availability. • Write data transformations in SQL/Python to generate data products consumed by Analytics, Marketing Operations, and Sales Operations teams. • Design, build, and operate large-scale Spark and PySpark workflows for batch and streaming data processing across Databricks and cloud environments. • Optimize Spark job performance — tuning partitioning, shuffle, caching, and resource allocation for production-grade reliability and efficiency. • Design, build, and manage data APIs in python using frameworks such as FastAPI. • Manage API runtime in AWS ecosystems- Lambda and RDS. • Monitor and optimize API , track observability via tools such as Data Dog or Splunk. • Champion, role model, and embed Samsara's cultural principles as we scale globally. • Provide mentorship to junior team members and deliver technical guidance, training, and knowledge-sharing across teams.

• Build large-scale ETL/ELT pipelines and analytical architectures within the GCP ecosystem. • Assess, plan, and drive enterprise migration programs across data, applications, and cloud platforms. • Help clients modernize their technology landscape and optimize legacy systems. • Enable scalable, cloud-native architectures aligned with business goals.

• Design, build, and maintain robust, scalable ELT/ETL data pipelines (batch and streaming) from various source systems into cloud data platforms and warehouses. • Optimize pipelines for performance, cost, reliability, and scalability. • Design and implement conceptual, logical, and physical data models (including dimensional modeling, star/snowflake schemas). • Build and maintain transformation layers using modern tools (e.g., dbt) to create clean, well-documented, analytics-ready datasets. • Write optimal SQL queries for data exploration, ad-hoc analysis, and troubleshooting. • Support the creation of reports, dashboards, and self-service analytics assets in collaboration with data analysts and business teams. • Translate business questions into data requirements and deliver actionable insights or datasets. • Monitor data pipelines and data delivery processes to ensure SLAs for timeliness, freshness, and accuracy are consistently met. • Proactively identify, troubleshoot, and resolve data issues impacting downstream consumers or business operations. • Manage incidents related to data availability and quality; participate in on-call rotations as needed. • Document data pipelines, models, lineage, and processes.

• Support SQL Server databases, including query development, troubleshooting, and maintenance. • Maintain and support ETL processes and data integrations. • Provide operational support for Azure services and cloud infrastructure. • Monitor system performance and resolve production issues. • Support enterprise applications, reporting platforms, and file transfer processes. • Collaborate with technical teams to ensure data availability and system reliability. • Support Windows and Linux server environments.