Senior Integration Engineer

About the Role

This is a high-ownership engineering role at a seed-stage AI supply chain startup focused on the CPG sector. You will own the integration layer that connects the platform's AI decision engine to the real-world systems where customer data lives: legacy ERPs, cloud data warehouses, object storage, FTP drops, and custom spreadsheets. Getting this layer right means AI-driven recommendations actually land in systems of record, reliably and at scale.

What You'll Do

• Build, extend, and maintain integrations across ERPs, cloud data warehouses, object storage, and custom data sources.
• Design and orchestrate near-realtime syncs that handle millions of records per customer without manual intervention.
• Go deep into each external API, including its quirks and undocumented behaviors, and build connectors that hold up against real customer data.
• Write round-trip integration tests that protect the full read-update-write lifecycle from data loss.
• Validate and cross-match data early in the pipeline to catch errors before they cause business harm.
• Build monitoring and alerting so failures are caught and triaged before customers notice.
• Work directly with CPG operators and their IT teams, owning integrations end to end from scoping through shipping and ongoing operations.
• Evolve the integration layer so connecting new, unseen data sources becomes a configuration exercise rather than a rebuild.

What We're Looking For

• 3 or more years of hands-on production experience building and shipping data pipelines and integrations in Python.
• Deep experience integrating third-party systems via REST, SOAP, and query-language APIs, including OAuth, rate limiting, pagination, and undocumented API quirks.
• Strong proficiency with the Python backend stack: FastAPI, SQLAlchemy, and Pydantic.
• Advanced SQL skills, including high-performance query writing and bulk upsert operations at scale (billions of records).
• Experience designing idempotent, re-runnable pipelines with clean fetch, validate, normalize, and upsert patterns.
• Experience building write-path integrations with safety rails, dry runs, failure capture, and full auditability.
• Experience building for operability: structured logging, sync-run tracking, alerting integrations, and failure attribution.
• Experience with cloud data warehouse platforms such as Snowflake, BigQuery, or Databricks.
• Experience with background task orchestration frameworks (such as Temporal, Hatchet, or similar) for scheduling reliable syncs.
• Bonus: NetSuite API experience, AWS services (S3, FTP), unstructured data ingestion, or legacy ERP integration background.
• Comfort working directly with enterprise customers and their IT teams in an end-to-end ownership model.