Finance Staff Data Engineer, Ai Native

Life360

Remote, US
Base: $190,000 to $280,500 usd (us); base: $220,00...
**
8+ years distributed data systems experience
Databricks and aws infrastructure expertise
Python sql spark proficiency
** Life360 is seeking a Staff Data Engineer to join their Finance Data Team, which focuses on data ingestion, processing, and reporting to support Finance and Accounting operations. The ideal candidate should have extensive experience with distributed data systems and be proficient in tools like Databricks, Python, and CI/CD practices. **

Job Summary

  • Life360 is a remote-first company building an AI-native culture where AI tools are integral to how the team builds and operates.
  • The Staff Data Engineer will architect scalable data ingestion and egress frameworks while enhancing CI/CD processes with observability and LLM-driven reviews.
  • The role requires deep ownership of SOX compliance, security posture in AWS/Databricks environments, and the ability to mentor engineers to elevate team rigor.

Matching Summary

Match Score: 75

** Life360 is seeking a Staff Data Engineer to join their Finance Data Team, which focuses on data ingestion, processing, and reporting to support Finance and Accounting operations. The ideal candidate should have extensive experience with distributed data systems and be proficient in tools like Databricks, Python, and CI/CD practices. **

Salary

Base: $190,000 to $280,500 USD (US); Base: $220,000 to $260,000 CAD (Canada); Equity included; Medical dental vision financial benefits included

Skills & Requirements

Must-have

  • 8+ years distributed data systems experience
  • Databricks and AWS infrastructure expertise
  • Python SQL Spark proficiency
  • dbt core infrastructure deployment
  • CI/CD pipeline architecture with GitHub Actions
  • Terraform infrastructure as code
  • SOX compliance and security controls

Nice-to-have

  • AI LLM usage for development velocity
  • Cursor Claude Code tool proficiency
  • Mentoring engineers on distributed systems
  • Building custom data connectors
  • LLM-driven code review capabilities
  • Proactive risk surfacing and tradeoff analysis

Key Requirements

  • 8+ years designing high-volume distributed data systems
  • Deep expertise with Databricks and AWS architecture
  • Strong proficiency in Python, SQL, and Spark
  • Hands-on experience with dbt infrastructure and deployment
  • Experience with Terraform and GitHub Actions
  • Knowledge of SOX compliance procedures

Work Rights

Not specified

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