Senior Analytics Engineer

About the role

About Extend:

Extend is revolutionizing the post-purchase experience for retailers and their customers by providing merchants with AI-driven solutions that enhance customer satisfaction and drive revenue growth. Our comprehensive platform offers automated customer service handling, seamless returns/exchange management, end-to-end automated fulfillment, and product protection and shipping protection alongside Extend's best-in-class fraud detection. By integrating leading-edge technology with exceptional customer service, Extend empowers businesses to build trust and loyalty among consumers while reducing costs and increasing profits.

Today, Extend works with more than 1,000 leading merchant partners across industries, including fashion/apparel, cosmetics, furniture, jewelry, consumer electronics, auto parts, sports and fitness, and much more. Extend is backed by some of the most prominent technology investors in the industry, and our headquarters is in downtown San Francisco.

About the Role:

Extend provides product and shipping protection to merchants and their customers, supporting the data and systems behind protection plans, claims, and payments.

You will design, build, and improve the data pipelines, integrations, and foundational data models that power Extend's analytics and financial systems. Working primarily in Snowflake, dbt, and AWS, you'll ensure data from internal systems, merchants, and external partners is reliable, accessible, and structured for downstream use.

You'll partner closely with Engineering, Analytics, Finance, and Operations to solve complex data challenges, improve our infrastructure, and establish best practices. This is a hands-on senior role for someone who combines strong SQL and data engineering skills with technical leadership and independent problem-solving.

What You’ll Do:

Data Architecture & Engineering. Design, build, and maintain scalable data pipelines and architecture across Snowflake, dbt, and AWS. Lead technical decisions around ingestion, transformation, orchestration, and data modeling, ensuring our infrastructure is reliable, performant, and built to scale.

Data Integrations & Foundational Modeling. Develop and improve integrations with internal systems, merchants, payment platforms, and external partners. Build well-structured, reusable dbt models that transform raw source data into trusted datasets for downstream analytics, financial systems, and reporting.

Data Quality & Governance. Establish standards for data testing, monitoring, validation, documentation, and governance. Implement automated controls to identify issues early, improve data integrity, and ensure data is traceable and reliable across systems.

Cross-Functional Partnership. Partner with Engineering, Analytics, Finance, Operations, and Financial Systems to understand business requirements, define data specifications, and ensure downstream teams have the reliable data they need. Communicate technical concepts and tradeoffs effectively to both technical and non-technical stakeholders.