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# Analytics Engineer

- **Company:** Life360
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $148,000.0 - $219,000.0
- **Contract:** Permanent contract
- **Skills:** Unity 3d, Computer-Aided Design, A/B Testing, Artificial Intelligence, Business Analytics Applications, Data Analysis, BigTable, BigQuery, Code Generation, Code Review, Cyber Security, Computer Programming, Continuous Delivery, Information Engineering, Data Governance, Data Infrastructure, Data Mart, Data Transformation, Data Warehousing, Cursor (Graphical User Interface Elements), Software Debugging, Dimensional Modeling, Python (Programming Language), Package Management Systems, Performance Tuning, Query Optimization, Raw Data, Standard Sql, SQL Databases, Tableau (Software), GitHub Copilot, Large Language Models, Snowflake, Data Build Tool (dbt), Git, Data Lakes, Kubernetes, Information Technology, Data Analytics, Performance Monitor, Virtual Agents, Looker Analytics, Software Version Control, Databricks
- **Published:** August 1, 2026
- **Apply:** https://www.builtincolorado.com/auth/login?destination=/job/senior-analytics-engineer/10487324

## About the Role

* Minimum 5+ years of experience in analytics engineering, data modeling, or similar roles working with enterprise-scale data, and demonstrated ownership of data products and cross-functional collaboration
 * Experience using AI/LLM coding assistants (for example, GitHub Copilot, Cursor, or Claude Code), with a disciplined approach to reviewing, testing, and owning generated code rather than accepting it at face value.
 * Expert-level SQL skills with deep understanding of query optimization and performance tuning
 * Extensive experience with dbt (data build tool) including testing, documentation, and package management
 * Strong programming skills in Python for data manipulation, automation, and custom analytics workflows
 * Strong understanding of dimensional modeling, star schemas, one big table, and other data modeling methodologies
 * Working knowledge of the Databricks platform, including SQL Warehouses, Delta Lake, and Unity Catalog; experience with other modern cloud data warehouses (Snowflake, BigQuery, or Redshift) is a plus and readily transferable.
 * Familiarity with orchestration frameworks and how analytics transformations are scheduled within broader data workflows
 * Experience working with version control systems (Git) and implementing CI/CD for analytics code
 * Strong business acumen and ability to translate business requirements into well-designed data models
 * Prior experience working with advertising, ad tech, or media data is preferred.
 * Understanding of data governance, privacy, and compliance requirements (GDPR, CCPA, and SOX)
 * Familiarity with BI tools (Tableau, Looker, Mode, or similar) and how analysts consume data
 * Strong ownership mindset with a passion for deeply understanding ambiguous business problems and translating them into clean, maintainable, and well-tested data models.
 * Excellent communication skills with ability to explain technical concepts to both technical and non-technical audiences
 * Dedication to data quality, documentation, and empowering others through self-service analytics
 * Bachelor's degree or equivalent experience in Computer Science, Information Security, or a related field

## Description

Design, build, and maintain scalable dbt transformation pipelines and dimensional data models on Databricks. Partner with data engineering and stakeholders to deliver trusted silver/gold datasets, implement data quality tests and monitoring, enable self-service semantic layers, and enhance LLM-driven tooling to accelerate analytics and automation.
The summary above was generated by AI
About Life360

Life360's mission is to keep people close to the ones they love. Our category-leading mobile app,Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 91.6 million monthly active users (MAU), as of September 30, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US and Canada) regardless of any specified location above.
We Are AI Native

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.

Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.
About The Team

The Analytics Data Engineering team's purpose is to design, build, and maintain scalable and efficient data infrastructure that empowers Life360 teams to make data-driven decisions. We transform raw data into reliable, accessible, and actionable insights, ensuring data quality, compliance, security, costs and performance at every step. We help teams across the business unlock the full potential of their data, driving operational excellence and strategic growth. We also push the boundaries of how work gets done by adopting AI tools that accelerate our development and expand what we can deliver to stakeholders, so families get faster, more reliable experiences.
About the Job, At Life360, we collect a lot of data: 60 billion unique location points, 12 billion user actions, 8 billion miles driven every single month, and so much more. As a Senior Analytics Engineer, you will be responsible for transforming this wealth of data into trusted, well-modeled datasets that power analytics, reporting, and data science initiatives across the organization. You should have a strong foundation in data modeling, SQL, and Python, deep understanding of business metrics, and a passion for making data accessible and understandable to stakeholders at all levels. Beyond modeling and analytics engineering, you will take on some data engineering responsibilities, working directly within our Databricks-based platform to help build and maintain the pipelines that feed the datasets you model., * Design and implement robust dimensional and relational data models that support analytical use cases across Product, Marketing, Operations, and Finance

 * Build and maintain scalable dbt transformation pipelines, ensuring high data quality, performance, and cost-efficiency from raw ingestion to business-ready outputs
 * Own the transformation and modeling of curated (Silver/Gold) datasets, ensuring clear contracts and traceability from raw to business-ready data.
 * Partner with data engineering to build and maintain data pipelines and Delta Lake tables within Databricks, including basic ingestion, transformation, and orchestration work.
 * Collaborate with data analysts, product analytics, data scientists, and business stakeholders to translate requirements into durable data products that support experimentation, A/B testing, and advanced analytics
 * Implement data quality tests, monitoring, SLAs, and alerting to ensure reliability of critical analytical datasets
 * Enhance our LLM development support capabilities - creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems.
 * Partner with Data Engineers to define and enforce data contracts, ensuring schema stability and minimizing downstream breakage
 * Establish and evangelize analytics engineering best practices, including version control, code review, testing standards, and documentation
 * Empower self-service analytics by building intuitive, well-documented data marts and semantic layers

Success in Year One

Within the first year in this role, the person hired will have built canonical gold and silver models for the reporting revamp and consolidation effort, serving as the source of truth across all business lines and products and reconciling cleanly against partner data. Building on that foundation, they will have automated revenue and performance reporting directly from these models, removing the manual overhead that currently sits between raw data and trusted numbers. They will have also delivered a semantic layer, enabling executives, Product, Finance, and Accounting to self-serve their own reporting and data requests without routing every question through the data team. Finally, they will have set up alerting for metric trend changes and anomalies, so issues surface proactively rather than being discovered after the fact.


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