Staff Data Engineer, Data Platform Core (AI Native)

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 validate data quality faster.
• Build and improve Databricks Genie chatbots that allow non-technical users to query data using natural language.
• Collaborate with product analytics and data science, applying engineering rigor to messy, unstructured data and transforming it into reliable, production-ready datasets.
• Contribute to infrastructure-as-code (Terraform/Atmos) for provisioning and managing cloud data infrastructure.

What We’re Looking For

• 10+ years working with high-volume data infrastructure.
• Core stack: Databricks, AWS (EMR, Kinesis/Kafka, S3), Apache Spark/Spark Streaming, Apache Airflow (MWAA), SQL, Python (Java/Scala is a plus).
• AI-native mindset: You already use LLM-based dev tools daily, not as a novelty, but as a force multiplier. You can evaluate when AI-generated code is correct, refactor prompts like you refactor code, and build agentic workflows that compound your team's output.
• Experience with data quality frameworks (Great Expectations, DQX, or similar): validation rules, schema enforcement, automated monitoring.
• Proven ability to architect logical/physical data models, optimize SQL, and tune system performance.
• Familiarity with IaC tools (Terraform) for cloud infrastructure provisioning.
• Strong communicator who works independently and ships with minimal supervision.
• BS in CS, Engineering, Math, or equivalent hands-on experience.

AI-Native Expectations

Daily use. Our engineers use Claude Code every day to scaffold pipelines, write and review code, generate tests, and draft documentation. Our codebase includes custom Claude skills that enforce team conventions, and we use Databricks Genie to answer common data questions for non-technical users.

Judgment and ownership. You own everything you ship, whether you or a model wrote it. You review AI-generated code as if you wrote it, test it as if it were going to production, and refactor it when it doesn't meet our standards.

Velocity. We expect AI fluency to show up as output: faster pipeline delivery, broader test coverage, and better documentation, without lowering quality.

Team leadership. You share what works, contribute to our shared AI tooling (Claude skills, agent workflows, prompts), and help other engineers get more out of their AI tools.

Continuous learning. AI tooling changes quickly. You stay current on new tools and techniques, try them on real work, and bring recommendations to the team.

Our Benefits

• Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer life and disability as well as supplemental plans for medical and dental for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Paid parental leave.
• Mental Wellness Program & Employee Assistance Program (EAP) for mental well-being.
• Generous time off: flexible PTO, companywide holidays throughout the year plus summer and winter shutdowns.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership and Tile trackers.

AI Usage: We use AI to help make our hiring process efficient. That said, every hiring decision is made by real Life360 hiring teams

Life360 Values

Our company’s mission-driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference

• Be a Good Person - We have a team of high integrity people you can trust.
• Be Direct With Respect - We communicate directly, even when it’s hard.
• Members Before Metrics - We focus on building an exceptional experience for families.
• High Intensity, High Impact - We do whatever it takes to get the job done.

Our Commitment to Belonging

Life360 is an equal opportunity employer. We don’t discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other legally protected status. We believe diverse perspectives make us better, and we’re building a workplace that reflects the communities we serve. Don’t meet every qualification? Apply anyway.

#LI-Remote

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