Senior Data Engineer II, AI Native

Life360 is a remote-first company building services that help people protect and stay connected with their families, pets, and belongings. The Senior Data Engineer II will enhance and maintain secure, scalable data lakehouse pipelines and systems supporting real-time analytics, machine learning, and experimentation. The role also involves data modeling, ML feature development, workflow automation, and collaboration with product, analytics, and data science teams.

Responsibilities:

• 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

Requirements:

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