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Salary: USD 155,000 - 170,000 / annual
Extend is a post-purchase commerce platform serving over 1,000 merchants with AI-driven solutions for customer service, returns management, fulfillment, and fraud detection. The company is backed by prominent technology investors and headquartered in San Francisco.
You will join the team building and maturing Extend's merchant integration platform. This platform ingests data from diverse merchant sources—each with unique schemas, formats, and delivery mechanisms—and transforms it into clean, consistent, trustworthy data for downstream systems. You'll work on an AWS serverless stack with a production event-driven backbone actively being expanded.
Key responsibilities include:
• Design and build anti-corruption layers that map and transform merchant data, isolating each merchant's uniqueness while keeping downstream data consistent and reusable.
• Accelerate merchant onboarding by building tooling and standards for partner teams, supporting merchant migrations, and taking on complex integrations yourself.
• Develop merchant-facing error reporting frameworks that turn validation and processing errors into clear, actionable reports for data providers and operators.
• Engineer resilient data boundaries with validation, reconciliation, and automated failure triage to catch bad data early and prevent silent data loss.
• Expand the event-driven architecture (Kafka, EventBridge, SNS), decoupling Step Functions and SQS orchestration and adding lifecycle webhooks for service and order events.
• Own reliability end-to-end: design through production, including monitoring, observability, data-quality checks, and reconciliation.
• Mentor team members and raise the bar through the work you ship, helping shape integration standards.
Requirements:
• 4–6 years in Data Engineering, Platform Engineering, or 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 defensive, correctness-focused engineering for external data boundaries.
• 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.
• Ownership mentality: identify problems early and drive work to completion without step-by-step guidance.
• Mentorship experience with a humble, collaborative approach.
• Bonus: experience designing clear, actionable error surfaces or reporting for external or non-technical consumers.
