Job Description

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.

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.
• Hands-on experience with dbt .
• 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.

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