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.
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.
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.
Visa sponsorship is available for this role.
On-site in New York, United States.
Job details are sourced from the employer's original posting.
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