Staff Data Engineer, Data Platform Core (AI Native)
Life360 · Remote, USA ; Remote, Canada · 2026-10-08
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 102.4 million monthly active users (MAU), as of June 30, 2026, 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 Data Platform Core team designs, builds, and maintains scalable data infrastructure that empowers Life360 to make data-driven decisions. We transform raw data into reliable, accessible, and actionable insights, ensuring data quality, compliance, security, cost efficiency, and performance at every step. By leveraging innovative technologies and best practices, we enable Product, Analytics, and Partners to unlock the full potential of data, driving operational excellence and strategic growth.
We are also an AI-native team. We embed AI tooling directly into our engineering workflows, from pipeline scaffolding to documentation generation, so our engineers ship faster and our data products improve continuously. If you believe the future of data engineering is human judgment amplified by AI, you'll fit right in.
About the Job
As a Staff Data Engineer, you will be a key driver in scaling Life360's data infrastructure to support a product trusted by millions of families worldwide. One of our major pipeline processes handles over 6 billion events per day and approximately 2 TB of data daily from high-throughput event streams via Kafka and Kinesis. We also run batch ingestion pipelines from MySQL, DynamoDB, and internal and external APIs. You'll own these critical pipelines end-to-end, from raw event ingestion through transformation to delivering clean, modeled datasets in our Databricks Lakehouse that power product decisions, analytics, and partner integrations. Our infrastructure runs on AWS, leveraging Databricks, Kafka, S3, Kinesis, and MWAA (Managed Workflows for Apache Airflow) for orchestration, along with many other AWS services. Beyond building and maintaining our own pipelines, we partner closely with Analytics Engineering, Data Science, and other teams across the organization, providing data infrastructure support and onboarding new and existing data sources into our bronze layer.
We also build chatbots that enable non-technical users to interact with data in natural language, automating common data questions and reducing the burden on engineering teams. This role sits at the intersection of platform reliability and engineering velocity, where your work directly unblocks other data teams, data scientists, analysts, and product teams. You'll also help shape how the team builds with AI, contributing to tooling and workflows that make every engineer more effective. You will architect new systems, tackle ambiguous data problems, and raise the bar for how we deliver data at scale.
For candidates based in the US, the salary range for this position is $190,000 to $280,500 USD. For candidates based out of Canada, the salary range for this position is 220,000 to 260,000 CAD. Note: Please be aware that the job title for positions in Canada will be "Developer" in lieu of "Engineer."
We take into consideration an individual's background, job-related knowledge, skills, and experience in determining final salary. Base pay may also vary based on geographic location, with US work locations falling into one of three geographic tiers.
Total compensation is inclusive of equity compensation in the form of Restricted Stock Units (RSUs), as well as a comprehensive benefits package, including medical, dental, vision, financial, and other benefits.
What You’ll Do
• Design and manage scalable data platforms powering real-time analytics, batch processing, and exploratory analysis, using AI-assisted development as the default workflow, not an afterthought.
• Own the full data lifecycle: ingestion, ETL, storage, and serving, building and iterating on pipelines with AI pair-programming tools (Claude Code) to accelerate delivery.
• Ingest data from diverse sources via both streaming (Kafka, Kinesis) and batch pipelines, unifying them into a consistent, queryable platform.
• Architect medallion-layer data models (Bronze/Silver/Gold) in Databricks, ensuring business needs are met with clean, well-documented schemas.
• Automate, test, and harden data workflows, writing AI-augmented tests, data quality checks, and CI/CD pipelines that catch issues before production.
• Build and maintain AI-ready tooling: craft prompts, slash commands, and agent workflows that let the entire team scaffold pipelines, generate documentation, and…
Skills asked for
- kafka
- mysql
- dynamodb
- databricks
- aws
- airflow
- data science
- ci/cd
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