Senior Data Engineer, Ads Data (AI Native)

Life360

10h • $129,000 - $192,000 • Remote

About The Position

The Senior Data Engineer will own Life360’s Ads Data platform on Databricks, improving existing pipelines and extending the platform to support growing demand for datasets, metrics, and self-serve access. The role works directly with analysts, ad strategists, and sales teams to turn business questions into reliable data products and maintain consistent definitions for core metrics.

The engineer will build and operate batch and streaming pipelines, Delta Lake tables, curated dbt models, and the semantic layer. They will improve performance, reliability, and cost efficiency; integrate data from advertising platforms and other systems; establish data quality and observability practices; manage infrastructure as code; and apply governance, privacy, and access controls. The role also includes mentoring engineers, contributing to the technical roadmap, and building tools and agents that help LLMs support development and system maintenance.

The team uses AI coding tools as a professional standard. The role calls for regular, substantive use of these tools, with careful review, testing, and ownership of generated work, as well as sharing effective practices and staying current with the tooling.

Requirements

• At least 5 years of experience in data engineering building production data platforms at enterprise scale, with demonstrated ownership of data products and cross-functional collaboration.
• Deep hands-on Apache Spark expertise (PySpark and/or Scala), including partitioning, shuffle behavior, joins, skew handling, caching, and diagnosing and tuning slow or costly jobs.
• Deep knowledge of Databricks, including Delta Lake, Unity Catalog, Jobs/Workflows, Databricks Asset Bundles, Structured Streaming, and SQL Warehouses; experience optimizing performance and cost using cluster and warehouse sizing, autoscaling, Photon, and serverless.
• Strong SQL and Python (or Scala) skills for pipeline development, automation, and query optimization.
• Production experience with dbt, including model design, testing, documentation, and incremental strategies, running on Databricks in CI/CD workflows.
• Hands-on Terraform experience managing cloud and data platform infrastructure as code, and AWS experience including S3, IAM, and networking fundamentals as they relate to data platforms.
• Experience with orchestration frameworks such as Airflow or Databricks Workflows, Git, CI/CD, and building reliable, observable pipelines.
• Understanding of data modeling, including dimensional modeling, star schemas, and medallion architecture, and experience building semantic layers or metric definitions.
• Experience inheriting, refactoring, and improving existing data models and pipelines with attention to reliability, maintainability, and backward compatibility for downstream consumers.
• Experience using AI/LLM coding assistants such as GitHub Copilot, Cursor, or Claude Code, with a disciplined approach to reviewing, testing, and owning generated code.
• Strong business acumen and communication skills, including translating requirements from analysts, ad strategists, and sales teams into data products and explaining technical concepts to non-technical audiences.
• Familiarity with data governance and compliance requirements such as GDPR, CCPA, and SOX, and with BI tools such as Domo, Tableau, or Looker.
• Bachelor’s degree or equivalent experience in Computer Science, Engineering, or a related field.

Nice To Haves

• Prior experience with advertising, ad tech, or media data, such as campaign delivery, attribution, audience, or revenue reporting.

Responsibilities

• Enhance, extend, and operate batch and streaming pipelines and Delta Lake tables on Databricks across ingestion, orchestration, storage, and serving.
• Partner with business analysts, ad strategists, and sales teams to translate their questions into durable data products and insights, including campaign performance, audience, and revenue reporting.
• Build and maintain dbt models and tests for curated Silver/Gold datasets, and own the semantic layer and core business metrics.
• Manage Databricks and AWS infrastructure as code using Terraform.
• Integrate and reconcile data from ad platforms, CRM, partner feeds, and internal systems, including migrations from legacy tools and reports.
• Implement data quality tests, monitoring, lineage, SLAs, alerting, and data contracts; lead root-cause analysis when data breaks.
• Tune Spark and Databricks workloads for performance and cost, including query plans, partitioning, shuffle and skew, and cluster sizing.
• Establish engineering best practices such as version control, CI/CD, code review, testing, and documentation; mentor engineers and help shape the team’s technical roadmap.
• Apply data governance, privacy, and access controls for PII and requirements including GDPR, CCPA, and SOX.
• Create tools, skills, and agents that provide LLMs with context and help debug, build, and maintain systems faster.
• Use AI coding assistants for substantive engineering work, review and test generated code, share effective practices with teammates, and stay current with relevant tools.

Benefits

• Medical, dental, vision, life, and disability insurance plans; medical, dental, life, and disability coverage details vary between US and Canadian employees.
• US 401(k) plan with company matching; Canadian RRSP with DPSP plan.
• Paid parental leave.
• Mental Wellness Program and Employee Assistance Program (EAP).
• Flexible PTO, companywide holidays, and summer and winter shutdowns.
• Learning and Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership and Tile trackers.
• Equity compensation in the form of Restricted Stock Units (RSUs).

What This Job Offers

• Job Type: Full-time
• Career Level: Senior