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 is looking for a Senior Data Platform Engineer to help build and mature our merchant integration platform. Every merchant sends us data differently, with its own schemas, formats, and delivery mechanisms, and this platform turns that variety into clean, consistent, trustworthy data our downstream systems rely on.

You’ll join the team that owns and supports the merchant integration platform. Internal partner teams use the platform to onboard enterprise merchants, so you will build the capabilities they depend on and take on the hardest integration and reliability work yourself. The work blends Solutions, Data, and Platform Engineering on an AWS serverless stack with a production event-driven backbone we’re actively expanding.

What You’ll Do

Build anti-corruption layers. Design the mapping and transformation systems that isolate each merchant’s uniqueness so downstream data stays consistent, delivered as reusable platform capabilities others build on.
Make onboarding faster and safer. Build the tooling and standards that let partner teams onboard merchants quickly, support merchant migrations onto current platform capabilities, and take on the complex integrations yourself.
Build out merchant-facing error reporting. Build on our failure-capture and file-return capabilities to deliver a framework that turns validation and processing errors into clear, actionable reports for data providers and the engineers operating the integration.
Engineer resilient data boundaries. Build the validation, reconciliation, and automated failure-triage that catch bad data early and prevent silent data loss, backed by alerting that teams trust.
Expand our event-driven architecture. Extend our production backbone (Kafka, EventBridge, SNS), decoupling more Step Functions and SQS orchestration and adding lifecycle webhooks for service and order events.
Own reliability end-to-end. Own your work from design through production, including the monitoring, observability, data-quality checks, and reconciliation that prove it works as designed.
Mentor and lead by example. Raise the bar through the work you ship and help shape the integration standards the whole team builds against.

What We’re Looking For

4-6 years in Data Engineering, Platform Engineering, or a closely related field.
Deep AWS serverless experience: Lambda, DynamoDB, Glue, Step Functions.
Hands-on experience with event-driven systems (Kafka, EventBridge, SNS) and fluency in Python and TypeScript.
Experience building and hardening large-scale data platforms and integrations, including the defensive, correctness-focused engineering that keeps external data boundaries reliable.
Experience building platforms and tooling that other engineers build on, beyond end-user features.
Comfort with data at rest and in motion: delivering clean data into a warehouse (Snowflake or similar) or data lake, and building reconciliation against it.
An ownership mentality. You identify problems early and drive work to completion without step-by-step guidance.