Senior Analytics Engineer

About this role

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app,Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 91.6 million monthly active users (MAU), as of September 30, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com .

Life360 is a Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US and Canada) regardless of any specified location above.

We Are AI Native

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.

Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About The Team

The Analytics Data Engineering team's purpose is to design, build, and maintain scalable and efficient data infrastructure that empowers Life360 teams to make data-driven decisions. We transform raw data into reliable, accessible, and actionable insights, ensuring data quality, compliance, security, costs and performance at every step. We help teams across the business unlock the full potential of their data, driving operational excellence and strategic growth. We also push the boundaries of how work gets done by adopting AI tools that accelerate our development and expand what we can deliver to stakeholders, so families get faster, more reliable experiences.

About the Job

At Life360, we collect a lot of data: 60 billion unique location points, 12 billion user actions, 8 billion miles driven every single month, and so much more. As a Senior Analytics Engineer, you will be responsible for transforming this wealth of data into trusted, well-modeled datasets that power analytics, reporting, and data science initiatives across the organization. You should have a strong foundation in data modeling, SQL, and Python, deep understanding of business metrics, and a passion for making data accessible and understandable to stakeholders at all levels. Beyond modeling and analytics engineering, you will take on some data engineering responsibilities, working directly within our Databricks-based platform to help build and maintain the pipelines that feed the datasets you model.

For candidates based in the US, the salary range for this position is $148,000 to $218,500 USD. For candidates based out of Canada, the salary range for this position is 171,500 to $201,000 CAD. We take into consideration an individual's background and experience in determining final salary; therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

AI-Native Expectations

The Analytics Data Engineering team leverages LLMs to support code generation, analysis, and other use cases. Your experience with AI / LLM usage should include managing code generation with a close eye on quality, standards, and testing, while owning the outputs as your own. Your work with and ability to leverage these tools (Claude, Cursor, CoPilot) will drive your velocity and ability to effectively work within our environment.

What You’ll Do

Primary responsibilities include, but are not limited to:

• Design and implement robust dimensional and relational data models that support analytical use cases across Product, Marketing, Operations, and Finance

• Build and maintain scalable dbt transformation pipelines, ensuring high data quality, performance, and cost-efficiency from raw ingestion to business-ready outputs

• Own the transformation and modeling of curated (Silver/Gold) datasets, ensuring clear contracts and traceability from raw to business-ready data.

• Partner with data engineering to build and maintain data pipelines and Delta Lake tables within Databricks, including basic ingestion, transformation, and orchestration work.

• Collaborate with data analysts, product analytics, data scientists, and business stakeholders to translate requirements into durable data products that support experimentation, A/B testing, and advanced analytics

• Implement data quality tests, monitoring, SLAs, and alerting to ensure reliability of critical analytical datasets

• Enhance our LLM development support capabilities – creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems.

• Partner with Data Engineers to define and enforce data contracts, ensuring schema stability and minimizing downstream breakage

• Establish and evangelize analytics engineering best practices, including version control, code review, testing standards, and documentation

• Empower self-service analytics by building intuitive, well-documented data marts and semantic layers

Success in Year One

Within the first year in this role, the person hired will have built canonical gold and silver models for the reporting rev

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