Director, Data Engineering – AI Native

🕒 Junho 5

🏄 California – Remoto

🏄 California – Remote

💵 $216.000 - $318.000 / ano

⏰ Tempo Integral

🔴 Especialista

🚰 Engenheiro de Dados

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Life360

SiteLinkedInTodas as Vagas

201 - 500 funcionários

Fundada em 2008

👥 B2C

📡 Telecomunicações

💰 Post-IPO Equity em 2022-11

B2C • Safety • Telecommunications

A Life360 é um aplicativo líder em segurança familiar que oferece um conjunto abrangente de serviços para segurança digital e de localização. Com a Life360, os usuários podem compartilhar sua localização facilmente, rastrear seus telefones e gerenciar medidas de segurança de direção, incluindo detecção de acidentes e assistência na estrada 24 horas por dia, 7 dias por semana. O aplicativo inclui recursos para segurança digital, como proteção contra roubo de identidade e alertas SOS, garantindo proteção e prevenção para cada membro da família. Os planos da Life360, que incluem opções gratuitas, Gold e Platinum, são projetados para atender diversas necessidades, oferecendo tranquilidade com ferramentas avançadas de segurança e coordenação. O aplicativo é confiado por milhões de usuários e altamente avaliado nas lojas de aplicativos por sua eficiência e confiabilidade na conexão entre membros da família e garantia de sua segurança.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• 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.