Director, Data Engineering – AI Native

Life360

Director of Data Engineering leading engineering in the Data and Analytics organization at Life360. Managing data from end to end, collaborating with technical and business teams.

Posted 6/5/2026full-timeRemote • California • 🇺🇸 United StatesLead💰 $216,000 - $318,000 per yearWebsite

Tech Stack

Tools & technologies

BigQueryETL

About the role

Key responsibilities & impact

Define and drive the technical roadmap across data platform, analytics engineering, and ads data infrastructure. Set the architectural vision for how data is ingested, transformed, modeled, and served at Life360.
Own the analytics engineering strategy end-to-end: dbt project structure, data modeling standards (dimensional, OBT, and semantic layer), testing and documentation practices, and the development workflow that analytics engineers use daily.
Oversee the data platform: Databricks infrastructure, compute optimization, pipeline orchestration, data lake architecture, and the reliability/observability stack that keeps it all running at consumer scale.
Drive toward a self-serve data experience where analysts and data scientists can answer their own questions without engineering bottlenecks—this is the outcome that ties platform and analytics engineering together.
Make strategic build vs. buy decisions across the data stack and manage vendor relationships (Snowflake, Databricks, Amplitude, and related tooling).
Drive data quality, governance, and documentation standards that make data trustworthy and self-service across the company.
Bring an AI native approach to data engineering: leverage AI tools to accelerate development cycles, evaluate AI-powered data quality and anomaly detection solutions, and ensure our data infrastructure supports ML/AI workloads and experimentation at scale.
Stay current on emerging technologies in the data and AI space and make pragmatic decisions about adoption—knowing when a new tool solves a real problem vs. when it’s a distraction.

Requirements

What you’ll need

8–10+ years of experience in data engineering, analytics engineering, or data platform roles at technology companies, with at least 5 years in people management.
3+ years managing managers; you know how to lead through others, set org-level direction, and scale teams.
Define and drive the architectural vision for end-to-end ELT/ETL processes, covering data ingestion, transformation, modeling, and serving at consumer scale.
Strong technical credibility across data platform and analytics engineering, combined with solid business acumen, consistently tying technical decisions to business impact.
Strong experience with dbt (data build tool): project structure, testing frameworks, documentation standards, CI/CD for data transformations, and how to scale dbt across multiple teams and domains.
Production experience with Databricks or equivalent lakehouse platforms (Snowflake, BigQuery) at consumer scale—including pipeline design, orchestration, reliability and compute optimization, cost management, and data lake architecture.
Demonstrated experience managing multiple teams or workstreams simultaneously (15+ people across distinct functions) at a technology company.
Strong track record of stakeholder management at the director/VP level—you’re comfortable saying no, explaining tradeoffs, and building trust with non-technical leaders.
Ability to distill technical complexity into language that non-technical stakeholders can understand and act on. You can run a crisp stakeholder review with a VP of Product as effectively as you can lead an architecture review with your engineers.
Proven ability to prioritize ruthlessly across competing demands from multiple business units—a skill sharpened by working in fast-paced tech environments.
Strong business acumen—you understand how product metrics, growth loops, and monetization models connect to data infrastructure decisions.
AI native mindset: you actively use AI tools in your own work and have a point of view on how AI changes data engineering practices, team productivity, and infrastructure requirements.

Benefits

Comp & perks

Competitive pay and benefits.
Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer 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.
Employee Assistance Program (EAP) for mental wellness.
Flexible PTO and 12 company wide days off throughout the year.
Learning & Development programs.
Equipment, tools, and reimbursement support for a productive remote environment.
Free Life360 Platinum Membership for your preferred circle.

ATS Keywords

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Hard Skills & Tools

data engineeringanalytics engineeringdata platformELTETLdata ingestiondata transformationdata modelingdata qualityAI tools

Soft Skills

people managementstakeholder managementcommunicationprioritizationbusiness acumenleadershipstrategic decision-makingtechnical credibilitytrust buildingdistilling technical complexity