Director of Data Engineering

About Life360

Life360's mission is to keep people close to the ones they love through its category-leading mobile app, Tile tracking devices, and Pet GPS tracker. Empowering members to protect loved ones, pets, and belongings, Life360 serves approximately 97.8 million monthly active users (MAU) across over 180 countries. Life360 has over 500 remote-first employees.

We are AI Native

Life360 is building an AI-native company where AI is integral to how we build and operate. AI tool usage during interviews varies by role. Recruiters will provide clear guidance.

About The Team

The Data and Analytics (DnA) organization is crucial for Life360's understanding of its members, measurement, and decision-making. We own the data platform, analytics engineering, data science, and analytics functions, ensuring reliable, well-modeled data and the tools to act on it across the company. We value clarity, directness, and building effective solutions.

About the Job

Life360 is seeking a Director of Data Engineering to lead the engineering half of the Data and Analytics organization. This senior leadership role owns data end-to-end, from source to consumption by humans and LLMs. You will manage a team of data & analytics engineers and managers, and set the strategic direction for our data, collaborating closely with leaders in data science, engineering, product analytics, and marketing analytics. The role requires technical credibility across both data platform engineering and analytics engineering. You will set technical direction, spot issues, and earn the trust of strong engineers. Data engineering at Life360 is a strategic partner, embedded in product and business decisions. You will lead people, align teams, translate technical complexity, and represent data engineering at the leadership table. As an AI-native company, this leader will leverage AI tools, explore AI-powered approaches, and build infrastructure supporting ML and AI workloads.

What You’ll Do

• Technical Strategy & Execution: Define and drive the technical roadmap for data platform, analytics engineering, and ads data infrastructure. Set the architectural vision for data ingestion, transformation, modeling, and serving. Own the analytics engineering strategy (dbt, data modeling, development workflow). Oversee the data platform (Databricks, orchestration, data lake, observability). Drive toward a self-serve data experience. Make strategic build vs. buy decisions and manage vendor relationships. Drive data quality, governance, and documentation standards. Adopt an AI-native approach to data engineering.
• Leadership & People Management: Lead and develop engineering managers and their teams. Coach managers on leadership, hiring, and talent development. Own workforce planning, headcount allocation, and hiring strategy. Build a cohesive engineering organization.
• Stakeholder & Cross-Functional Partnership: Serve as the primary point of contact for data engineering across Product, Engineering, Finance, Marketing, and executive leadership. Manage intake and prioritization. Represent data engineering in leadership forums. Build strong partnerships with Analytics and Data Science.
• Business Impact: Understand Life360’s business deeply and prioritize engineering work that drives business impact. Partner with product and business teams to ensure data infrastructure supports experimentation and decision-making. Own budget and cost management for data engineering infrastructure.

What We’re Looking For

• Must-Haves: 8-10+ years in data engineering, analytics engineering, or data platform roles with at least 5 years in people management. 3+ years managing managers. Define and drive architectural vision for end-to-end ELT/ETL processes. Strong technical credibility across data platform and analytics engineering, combined with solid business acumen. Strong experience with dbt. Production experience with Databricks or equivalent lakehouse platforms at consumer scale. Demonstrated experience managing multiple teams (15+ people) at a technology company. Strong track record of stakeholder management at the director/VP level. Ability to distill technical complexity for non-technical stakeholders. Proven ability to prioritize ruthlessly. Strong business acumen. AI-native mindset.
• Nice-to-Haves: Experience at a consumer mobile, subscription-based, or marketplace technology company. Hands-on experience with Databricks, Amplitude, Statsig, dbt. Experience building or managing ads data infrastructure. Experience with real-time data streaming. Track record of implementing AI/ML-powered approaches. Experience managing remote-first or distributed engineering teams. Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.

Compensation:

• US Salary Range: $216,000 to $318,000 USD.
• Canada Salary Range: $251,000 to $295,000 CAD.
• Compensation depends on geographic location, job-related knowledge, skills, and experience. Includes equity and a wide range of benefits (medical, dental, vision, financial, etc.).