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Senior Data Engineer – AI Native
Life360Senior Data Engineer developing scalable data infrastructure for Life360's analytics. Driving data-driven decisions for a product trusted by millions of families worldwide.
Tech Stack
Tools & technologiesAirflowApacheAWSCloudETLJavaKafkaPythonScalaSparkSQLTerraform
About the role
Key responsibilities & impact- 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
What you’ll need- 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.
Benefits
Comp & perks- Medical, dental, vision, life and disability insurance plans (100% paid for US employees).
- 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.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data platformsETLdata ingestiondata modelingSQLPythonApache SparkApache Airflowdata quality frameworksinfrastructure-as-code
Soft Skills
strong communicatorindependent workminimal supervisioncollaborationengineering rigorproblem-solvingadaptabilityattention to detailcritical thinkingcreativity
Certifications
BS in Computer ScienceBS in EngineeringBS in Math