About The TeamThe Finance Data Team sits at the intersection of Finance & Accounting teams and Life360's data. We provide the data ingestion / processing / reporting needed by our partner teams in Finance & Accounting to enable their work and ensure SOX compliance with rigor. We push the envelope on how work is done through implementation of AI tools and capabilities to enhance our own pace of development and capabilities that we deliver to our stakeholders.
About the JobWe are hiring a Senior Finance Analytics Engineer on the Finance Data Team to support data modeling, reporting, and designing data products for an AI-native consumption model.
Most analytics engineering teams design for humans writing SQL in a BI tool. We design for both humans and agents. Our models, metrics, and documentation are consumed by Finance & Accounting analysts, by Claude, and by agents working through MCP against our Databricks environment. Semantic clarity, metadata quality, model contracts, and the documentation flywheel across dbt, Databricks, Confluence, and the semantic layer all matter more in this environment than they do in most.
Your work will cover: dbt model design, semantic layer and metrics definitions, documentation, testing, and contributing to our AI native development capabilities. This is a senior individual contributor role. You will not be expected to build AI infrastructure or MCP servers, but you should understand how agents consume the data and documentation you produce, and design accordingly.
This role reports to the Senior Manager of Finance Analytics Engineering, supporting the Finance Data Team that owns the Finance Data Warehouse.
The US-based salary range for this position is $103,500 to $192,000. We take into consideration an individual's background and experience in determining final salary - therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.
What You'll DoAnalytics Engineering- Design and build dbt models that serve as the source of truth for Finance & Accounting reporting, planning, and analysis.
- Partner directly with stakeholders in Finance, Accounting, Revenue, and FP&A to define metrics, shape requirements, and translate business logic into well-structured models.
- Write and optimize complex SQL against our Databricks environment with attention to accuracy.
- Uphold and evolve patterns for model design, testing, versioning, and data contracts across the dbt project.
Designing for AI Consumption- Design the semantic layer and metrics definitions (MetricFlow, Cube, or equivalent) that both humans and agents query against.
- Drive the documentation flywheel across dbt, Databricks, Confluence, and the semantic layer so that models, columns, and metrics are legible to LLMs and analysts alike.
- Design model grain, naming, and structure so an agent can find what it needs in the warehouse without a human guide.
- Use AI tooling (Claude Code, Cursor, and our internal capabilities) as a daily part of your own development workflow, and feed real signal back to the team on what design choices make agents more or less effective.
Operations & Compliance- Build and operate within our SOX-controlled CI/CD environment, with no direct human touches to production.
- Maintain documentation and auditability of the data pipelines you own.
- Participate in code review and approval workflows for SOX-controlled change management.
AI / LLM UsageThe Finance Data Team leverages LLM's to support code generation, analysis, and other use cases.
- Cursor / Claude Code.
- Other tools (Wispr Flow, Claude & Claude Cowork, Gemini / Codex).
Your experience with AI / LLM usage should include managing code generation with a close eye on quality, standards, and testing - owning the outputs as your own. Your work with and ability to leverage these tools will drive your velocity and ability to effectively work within our environment.
What We're Looking ForRequired Experience- 4+ years of analytics engineering experience, including deep hands-on work with dbt (dbt core strongly preferred).
- 4+ years of SQL experience in an MPP environment (Databricks, Snowflake, Redshift, Trino, or equivalent), with a strong track record of writing performant and maintainable transformations.
- 1+ years designing data products for AI consumption: semantic layer work, MetricFlow or Cube, metrics definitions, model contracts, or documentation patterns built with LLM consumers in mind.
- Hands-on experience using Claude Code, Cursor, or equivalent AI-enabled development tools as part of your daily workflow.
- Strong command of semantic modeling and metrics layer design.
- Designing dbt projects at scale: model organization, testing strategy, documentation standards, model versioning, and contracts.
- Familiarity with MCP servers and how agents consume warehouse data and metadata, enough to design models and docs that work well for both humans and agents.
- Strong written communication: you can write documentation that a stakeholder, a teammate, or an LLM can all use effectively.
- Finance or Accounting domain experience.
Additional Preferred Experience- Working in a SOX-controlled environment with formal change management.
- 1+ years of Python for scripting, API integration, and automation.
- 1+ years of Airflow.
- Databricks platform specifically, including Unity Catalog.
- Familiarity with Terraform, GitHub Actions, or Atlantis for infrastructure and CI/CD.
What Sets You Apart- You think about data models as products with consumers, and you treat documentation and semantic clarity as part of the deliverable rather than an afterthought.
- You have opinions about what makes a warehouse legible to an agent, and you can defend them.
Soft Skills- Comfort with ambiguity and the judgment to make progress when requirements are not fully defined.
- Ability to translate technical concepts for Finance & Accounting stakeholders who may not have a technical background.
- Self-direction: you can spot what needs doing and move it without constant guidance.
- Strong collaboration across Data Engineering, AI Engineering, and Finance teams.
Our Benefits- Competitive pay and benefits
- Medical, dental, vision, life and disability insurance plans (100% paid for employees)
- 401(k) plan with company matching program
- Mental Wellness Program & Employee Assistance Program (EAP) for mental well-being
- Flexible PTO, 13 company-wide days off throughout the year
- Winter and Summer Weeklong Synchronized Company Shutdowns
- Learning & Development programs
- Equipment, tools, and reimbursement support for a productive remote environment
- Free Life360 Platinum Membership for your preferred circle
- Free Tile Products
