Sr. Data Engineer - US (Remote)

Role Overview

As a Sr. Data Engineer (US Remote), you’ll be a technical leader helping shape platform architecture and drive AI-powered product delivery. The role focuses on building high-throughput streaming data systems and raising the bar for what a small, AI-augmented engineering team can accomplish.

Responsibilities

• Build and scale streaming pipelines
  • Ingest and process 400M+ MLS updates monthly across 350+ integrations.
  • Use Airflow, Spark Streaming, Kafka, and Iceberg to ensure reliability, performance, and data correctness.
• Create production-grade real estate datasets
  • Design and maintain datasets that power core product experiences.
  • Balance freshness, accuracy, and cost.
• Improve data quality and observability
  • Implement data quality checks, monitoring, and alerting to detect issues early and reduce downstream impact.
• Use AI to enhance data operations
  • Contribute to AI-driven tooling for triage, debugging, and resolving data quality issues, reducing manual work.

Requirements

• 6+ years professional experience in data engineering or software engineering.
• Strong experience with distributed streaming data processing, including Spark/PySpark and Kafka.
• Proficiency in Python (with Pydantic preferred).
• Experience building and maintaining pipelines on AWS using Airflow, Spark Streaming, and Iceberg.
• Solid data modeling skills for large-scale datasets.
• Familiarity with event-driven systems and ingestion patterns (e.g., Kafka, SQS).
• Experience implementing data quality checks, monitoring, and debugging data issues.
• Proven ability to lead high-impact initiatives from concept through production in a SaaS environment.
• Expert-level software design principles and experience with multi-tenant platform architectures.

Nice-to-Haves

• Use Claude Code as a core part of your workflow.
• Familiarity with Node/TypeScript.
• Interest in applying AI/ML or automation to improve data workflows.

AI/Engineering Culture

• You build with AI daily and have strong, grounded views on how AI changes system design and engineering culture.
• Clear communication with product/design/executive stakeholders and comfort operating in ambiguity and fast change.