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Senior Data Engineer II, AI Native

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Remote from
USA, Canada
Salary
USD 148k–216,500 / yr
Employment
Full Time
Experience
Senior
Published
Apply before
30 Oct 2026
Listing views
154
Application actions
8
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AI Summary

The role, at a glance.

Life360 is hiring a senior data engineer to design, operate, and improve distributed data pipelines and lakehouse systems supporting real-time analytics, experimentation, and machine learning. The role requires ownership of ingestion, ELT, storage, data modeling, workflow reliability, and ML-related data features at very large scale. Core technologies include Python, SQL, dbt, Spark or Presto/Trino, Databricks or another cloud warehouse/lakehouse, orchestration, CI/CD, and infrastructure as code. This is a remote-first full-time role available in the United States and Canada, with strong expectations for autonomous execution, cross-functional partnership, and responsible use of LLM tooling.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThis is a senior-level, high-scale platform role requiring deep hands-on expertise across distributed processing, cloud lakehouse architecture, data modeling, reliability, and developer tooling. The team explicitly operates in a high-ambiguity, high-intensity environment and expects engineers to independently create clarity and own outcomes.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$182,250
US market range$145k–$220k
AI insightThe disclosed US base-salary range is $148,000–$216,500 per year, with a midpoint of $182,250. This is broadly competitive for a US senior data engineer working on large-scale cloud data platforms; an estimated US market range is $145,000–$220,000 annually, varying by location, scope, and depth of distributed-systems expertise. The posting also discloses a separate Canadian range of CAD 171,500–201,000; the structured salary fields represent the explicitly stated US range in USD.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a scalable pipeline for high-volume location events that supports both real-time analytics and downstream ML use cases?

I would separate ingestion, stream processing, durable storage, and serving concerns. Events would be validated and schema-versioned at ingestion, processed through a streaming layer with idempotency and late-event handling, and stored in partitioned lakehouse tables optimized for both incremental transformations and analytical reads. I would define data-quality checks, lineage, retention rules, and curated feature-ready datasets so real-time and batch consumers can use governed data consistently.

Describe how you have used dbt to improve the reliability and maintainability of an analytics platform.

I organize dbt projects into clear staging, intermediate, and mart layers, with documented contracts and ownership for critical models. I use incremental materializations where appropriate, tests for uniqueness, referential integrity, freshness, and accepted values, and CI to run selective builds and tests on pull requests. I also monitor run performance and failures, treating dbt models as production software rather than ad hoc SQL.

What factors do you consider when optimizing Spark workloads on a lakehouse platform?

I begin with workload characteristics, data size, skew, partitioning, file sizes, join patterns, and the physical plan. Typical improvements include filtering early, choosing appropriate partition keys, mitigating skew with salting or adaptive execution, avoiding unnecessary shuffles, compacting small files, and using efficient columnar formats. I validate changes through measured runtime and cost improvements while ensuring correctness and reproducibility.

How do you evaluate and safely incorporate LLM-generated code into production data engineering work?

I use LLMs to accelerate drafting, exploration, and refactoring, but I verify all outputs myself. That includes reviewing logic, security implications, performance characteristics, data edge cases, and consistency with project conventions; then I add or update automated tests and run the code in an appropriate non-production environment. The model can improve velocity, but ownership, validation, and production accountability remain with the engineer.

Tell us about a time you brought clarity to an ambiguous data problem involving multiple stakeholders.

I would start by identifying the decision or user outcome the work must support, then document the current state, unknowns, data definitions, risks, and proposed milestones. I bring product, analytics, and data science partners together to agree on a minimum viable contract and success metrics, while making tradeoffs visible. Regular written updates, clear ownership, and iterative delivery help convert ambiguity into a reliable plan without waiting for perfect requirements.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

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 & Analytics team is building Life360’s next-generation data platform — powering real-time decision-making, experimentation, ML, and large-scale analytics. We operate at significant scale and complexity in a high-ambiguity environment, and we expect engineers to own problems, drive clarity, and raise the bar across the org.

We’re looking for a high-intensity engineer who wants to envision, design, and build high-impact data products with cutting-edge tools — all while keeping our members ahead of the metrics. You’ll become the go-to person for data products across the business, joining a collaborative team that communicates openly, celebrates wins together, and is committed to helping everyone do their best work.

About the Job

At Life360, we collect a lot of data: tens of billions of unique location points, tens of billions of user actions, billions of miles driven every single month, and so much more. As a Senior Data Engineer II, you will enhance and maintain our data processing and storage pipelines for a robust and secure data lakehouse. We’re looking for a strong engineering background — and just as important, a genuine desire to take ownership and make our data systems world class.

The US-based salary range for this position is $148,000 to $216,500. 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, 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

Primary responsibilities include, but are not limited to:

  • Design, build, and maintain scalable, distributed data pipelines and systems — from ingestion through ELT to storage — supporting streaming and batch processing for real-time analytics, ML, and experimentation.
  • Automate, test, and harden data workflows to ensure reliability at scale.
  • Architect logical and physical data models that meet evolving business needs.
  • Build and maintain features for ML models.
  • Collaborate with product, analytics, and data science teams to turn data into value.

What We’re Looking For

  • 5+ years of experience working with high volume data infrastructure.
  • Deep expertise with a modern cloud data warehouse or lakehouse platform (Databricks preferred; Snowflake, BigQuery, or similar also considered) on a major cloud provider (AWS, GCP, or Azure).
  • Proficient in Python and SQL, with the ability to write and optimize complex queries.
  • Must have hands-on experience with dbt, ownership of dbt models.
  • Experience with large-scale data processing using Spark and/or Presto/Trino.
  • Strong grasp of data modeling, partitioning strategies, storage formats, and analytical workload optimization.
  • Hands-on experience leveraging LLMs for code generation, analysis, and related work — including reviewing AI-generated output with a close eye on quality, standards, and testing, and owning it as your own.
  • Experience with modern data engineering tooling — orchestration (Airflow, Databricks Workflows), CI/CD (GitHub Actions), and infrastructure-as-code (Terraform, DABs).
  • BS in Computer Science, Information Systems, Management Information Systems, Statistics, Mathematics, Data Science, Engineering (Computer, Electrical, or Software), or a related quantitative field.

AI-Native Expectations

  • The 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 — owning the outputs as your own. Your work with and ability to leverage these tools will drive your velocity and ability to effectively work within our environment.

Nice to Have

  • Experience working with an experimentation framework.
  • Experience designing and maintaining real-time streaming architectures.

Our Benefits

  • Medical, dental, vision, life and disability insurance plans (100% paid for employees)
  • Paid parental leave
  • 401(k) plan with company matching program
  • 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 Tile trackers

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 Diversity

We believe that different ideas, perspectives and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us closer to our customers and the communities we serve. We strive to create a workplace that reflects the communities we serve and where everyone feels empowered to bring their authentic best selves to work.

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status.

We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful. Even if you don’t meet 100% of the below qualifications, you should still seriously consider applying!

#LI-Remote

Apply now >

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