Senior Data Engineer (AI Native)

Life360 is a company dedicated to keeping families close through innovative mobile applications and services. They are seeking a Senior Data Engineer to scale their data infrastructure, manage data pipelines, and leverage AI tools to enhance data-driven decision-making for millions of users worldwide.

Responsibilities:

• Design and manage scalable data platforms powering real-time analytics, batch processing, and exploratory analysis, using AI-assisted development as the default workflow, not an afterthought
• Own the full data lifecycle: ingestion, ETL, storage, and serving, building and iterating on pipelines with AI pair-programming tools (Claude Code) to accelerate delivery
• Ingest data from diverse sources via both streaming (Kafka, Kinesis) and batch pipelines, unifying them into a consistent, queryable platform
• Architect medallion-layer data models (Bronze/Silver/Gold) in Databricks, ensuring business needs are met with clean, well-documented schemas
• Automate, test, and harden data workflows, writing AI-augmented tests, data quality checks, and CI/CD pipelines that catch issues before production
• Build and maintain AI-ready tooling: craft prompts, custom slash commands, and agent workflows that let the entire team scaffold pipelines, generate documentation, and validate data quality faster
• Build and improve Databricks Genie chatbots that allow non-technical users to query data using natural language
• Collaborate with product analytics and data science, applying engineering rigor to messy, unstructured data and transforming it into reliable, production-ready datasets
• Contribute to infrastructure-as-code (Terraform/Atmos) for provisioning and managing cloud data infrastructure

Requirements:

• 5+ years working with high-volume data infrastructure
• Core stack: Databricks, AWS (EMR, Kinesis/Kafka, S3), Apache Spark/Spark Streaming, Apache Airflow (MWAA), SQL, Python (Java/Scala a plus)
• AI-native mindset: You already use LLM-based dev tools daily, not as a novelty, but as a force multiplier. You can evaluate when AI-generated code is correct, refactor prompts like you refactor code, and build agentic workflows that compound your team's output
• Experience with data quality frameworks (Great Expectations, DQX, or similar): validation rules, schema enforcement, automated monitoring
• Proven ability to architect logical/physical data models, optimize SQL, and tune system performance
• Familiarity with IaC tools (Terraform) for cloud infrastructure provisioning
• Strong communicator who works independently and ships with minimal supervision
• BS in CS, Engineering, Math, or equivalent hands-on experience