Senior Data Engineer II

Who we are

Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara we are helping improve the safety efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP these industries are the infrastructure of our planet including agriculture construction field services transportation and manufacturing and we are excited to help digitally transform their operations at scale.

Working at Samsara means youll help define the future of physical operations and be on a team thats shaping an exciting array of product solutions including Video-Based Safety Vehicle Telematics Apps and Driver Workflows and Equipment Monitoring. As part of a recently public company youll have the autonomy and support to make an impact as we build for the long term.

About the role

As a Senior Data Engineer II (P50) you are an experienced data engineer who consistently delivers highimpact outcomes across both short and long time horizons leading domains that span multiple services and business areas. You combine deep data engineering expertise with strong business acumen to guide the roadmap and architecture for your area elevate the teams overall capabilities and act as a senior escalation point for technical and operational issues.

You spearhead the endtoend data solutionsfrom ingestion and modeling through quality observability and consumptionwhile mentoring P20/P30 engineers and driving process and automation improvements across the team.

This hybrid position requires 3 days per week in our Bangalore office and 2 days working remotely. This position requires working hours in IST. Relocation assistance will not be provided for this role.

What youll do

• Lead endtoend data solutions across multiple subject areas and services from requirements and design through implementation rollout and ongoing ownership.
• Architect build and maintain largescale productiongrade data pipelines (batch and/or streaming) using modern data lake and warehouse technologies (e.g. Databricks Delta cloud data platforms) and industrystandard ETL/ELT patterns.
• Design robust data models and curated golden datasets that power analytics dashboards and data science use cases including facts dimensions snapshots and SCDs.
• Own data quality reliability and SLAs for your domains: define contracts implement validation and monitoring and drive rootcause analysis and longterm fixes for data incidents.
• Influence team and crossfunctional roadmaps and OKRs by translating business goals into multiquarter technical plans tradeoffs and investment proposals.
• Partner closely with crossfunctional teams (e.g. Finance Sales Ops RevOps Product Data Science & Analytics) to understand requirements and deliver scalable data solutions that unlock insights and automation.
• Lead incident response and complex technical investigations for your areas coordinating across teams driving clear communication and ensuring durable remediation.
• Mentor and uplevel other engineers providing code and design reviews pairing and structured feedback to grow the teams technical mastery and operational excellence.
• Improve processes documentation and tooling for data development testing deployment and observability; standardize best practices across BizTech Data & Integrations.
• Champion Samsaras cultural principlesFocus on Customer Success Build for the Long Term Adopt a Growth Mindset Be Inclusive and Win as a Teamin how you design systems and collaborate across the company.

Minimum qualifications

• 10 years of relevant experience in data engineering or closely related roles with demonstrated impact and career progression.
• Bachelors or Masters degree in Computer Science Software Engineering Electrical Engineering Computer Engineering or related discipline.
• Expert-level data engineering skills including ETL/ELT data modeling and working with large-scale cloud-based data lake/warehouse stacks and modern tooling (e.g. Spark SQL engines orchestration frameworks).
• Strong programming skills in SQL and at least one general-purpose language (e.g. Python) with experience building and maintaining production-grade pipelines and reusable frameworks.
• Proven experience designing and operating critical data models and curated datasets for analytics reporting and/or ML use cases including performance tuning and cost optimization.
• Demonstrated experience in AI/ML systems including building deploying or supporting machine learning pipelines feature engineering workflows and integrating predictive or generative models into production data systems.
• Hands-on experience with AI application and agent development including designing and deploying intelligent agents workflow automation or LLM-powered applications (e.g. retrieval-augmented generation tool-using agents conversational systems) with a focus on scalability observability and reliability.
• Demonstrated ability to lead multi-stakeholder projects over 2 quarters managing tradeoffs between technical quality speed and business impact.
• Solid knowledge of Databricks features and administration including Unity Catalog cluster management security troubleshooting root-cause analysis and performance optimization.
• Strong communication and collaboration skills including clear written design docs and effective communication with senior stakeholders and cross-functional partners.
• Track record of mentoring and acting as an escalation point for more junior engineers or analysts.

Experience with the following:

• 5 years in Python SQL.
• Exposure to ETL tools such as Fivetran DBT or equivalent.
• API: Experience with Python-based API frameworks for building and serving data/AI pipelines.
• RDBMS: MySQL AWS RDS/Aurora MySQL PostgreSQL Oracle MS SQL Server or equivalent.
• Cloud: AWS Azure and/or GCP.
• Data warehouse: Databricks Google BigQuery AWS Redshift Snowflake or equivalent.
• Experience integrating AI/ML platforms and tooling (e.g. MLflow feature stores vector databases model serving infrastructure) into data ecosystems.
• Familiarity with LLM ecosystems including prompt engineering embeddings vector search and evaluation frameworks for AI applications.
• Hands-on experience with modern AI developer tools and assistants such as Claude Cursor GitHub Copilot and ChatGPT for accelerating development code generation debugging and workflow automation.
• Experience in SaaS B2B or data-heavy product environments especially where IoT telemetry or event-driven data plays a central role.
• Hands-on experience with Databricks or similar Spark-based platforms Delta/Parquet data lakes and modern data orchestration tools.
• Background working with finance sales or revenue operations data and comfort modeling business processes such as bookings billings and pipeline.
• Prior experience driving cross-team data initiatives (e.g. standardizing metrics centralizing business logic or implementing shared data governance frameworks)

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