Senior Data Platform Engineer, Enterprise Merchant Integrations

Extend provides AI-driven post-purchase solutions for retailers, including customer service, returns, fulfillment, protection, and fraud detection. The Senior Data Platform Engineer will build and mature the merchant integration platform, developing reliable data transformations, onboarding tools, error reporting, validation, reconciliation, and event-driven architecture while owning production reliability and mentoring teammates.

Responsibilities:

• 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

Requirements:

• 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
• Mentorship experience, with a humble, collaborative approach
• experience designing clear, actionable error surfaces or reporting for external or non-technical consumers