Staff Data Engineer

Life360 is a company dedicated to keeping people close to their loved ones through innovative technology. They are seeking a Staff Data Engineer to drive the evolution of their data architecture, ensuring it is resilient and scalable while mentoring other engineers and raising engineering standards.

Responsibilities:

• Identify structural weaknesses and eliminate operational fragility
• Define clear ingestion, validation, and testing standards across the platform
• Drive ambiguous initiatives from concept to production-ready outcomes
• Produce decisive technical artifacts and recommendations that enable leadership decisions
• Raise the engineering bar across CI/CD, observability, cost efficiency, and documentation discipline
• Architect and evolve scalable, cost-efficient data platforms for real-time and batch analytics
• Own data systems end-to-end — ingestion, streaming, transformation, storage, and serving
• Design and implement distributed data processing systems using Spark and Databricks on AWS
• Build and optimize pipelines using Airflow and modern orchestration frameworks
• Define and enforce engineering standards for CI/CD, infrastructure-as-code, testing, and observability
• Establish clear ingestion and integration boundaries that eliminate single points of failure
• Proactively surface risks, dependencies, and tradeoffs before they impact delivery
• Produce clear technical artifacts and recommendations for stakeholders and leadership
• Design logical and physical data models balancing flexibility, performance, governance, and scalability
• Partner closely with Analytics Engineering, Data Science, ML Engineering, and Data Analytics to support high-quality silver/gold modeling
• Harden pipelines with monitoring, alerting, SLAs, and recovery mechanisms
• Mentor engineers and elevate distributed systems rigor across the team

Requirements:

• 8+ years designing and operating high-volume distributed data systems in production
• Deep expertise with a cloud data platform (Databricks preferred) and AWS, including performance tuning and cost optimization
• Strong proficiency in Python, SQL, and Spark for large-scale processing
• Hands-on experience with dbt and understanding of how platform decisions impact downstream modeling
• Strong grasp of data modeling, partitioning strategies, storage formats, and analytical workload optimization
• Experience with Airflow
• Experience with modern CI/CD practices (GitHub Actions, Terraform)
• Experience designing and maintaining real-time streaming architectures
• Demonstrated ability to independently scope ambiguous problems and drive them to decisive outcomes
• Track record of proactively escalating risks and closing long-running efforts with clear recommendations
• Experience defining ingestion validation standards and implementing data quality controls
• Proven ability to reduce operational fragility and eliminate single points of failure
• Strong systems design skills across distributed and event-based architectures
• Demonstrated technical leadership influencing cross-team architectural decisions
• Excellent communication skills across engineering, analytics, product, and executive stakeholders
• BS in Computer Science, Engineering, Mathematics, or equivalent experience