[Hiring] Full Stack Engineer (Data Engineering Focus) @GNO Partners

Role Description

This role is full-stack, but with a clear lean toward data engineering. You'll:

• Design and build the data pipelines that pull from Amazon SP-API and Ads API into our Postgres warehouse — handling rate limits, retries, schema evolution, and the messy realities of vendor APIs.
• Architect ingestion, transformation, and aggregation layers that power our reporting tools.
• Build new report tools end-to-end alongside the rest of the engineering team — you're not only on pipelines.
• Help us scale our data layer as we move from per-client manual uploads to automated, multi-tenant data flow.
• Contribute to our AI insights layer — feeding clean, structured data into LLM-powered analysis.

Qualifications

• 3–5 years of full-stack experience, with a demonstrable track record of building data pipelines in production.
• Strong with TypeScript, Node.js, NestJS, and React.
• Deep comfort with Postgres / Supabase — partitioning, indexing, query optimization, handling large datasets.
• Hands-on experience with AWS: S3, Lambda, SNS, SQS, EC2. Bonus for orchestration tools (Step Functions, EventBridge, Airflow, Temporal, etc.).
• Experience integrating with third-party APIs at scale — pagination, rate limiting, backfills, incremental sync.
• Basic familiarity with AI agentic systems — you've worked with or explored LLMs, tool-use, or agent frameworks.
• Pragmatic and product-aware — you understand pipelines exist to serve user-facing features, not for their own sake.

Requirements

• Direct experience with Amazon SP-API and/or Ads API.
• Background with ETL frameworks, streaming systems (Kafka, Kinesis), or workflow engines (Temporal, Airflow).
• Experience with data quality tooling, observability, or pipeline monitoring.

Benefits

• You'll own the data backbone of a platform that's actively scaling.
• High-leverage work — every pipeline you build directly enables new product surface area.
• Clear path to work across pipelines, product, and AI as the platform evolves.