🧠 Data Engineer (Integrations & Data Quality)

🌍 Location & Work Setup🌎 Remote – Latin America💼 Full-time | B2B Contractor⏰ 7 working hours/day🌴 20 PTO days/year + national holidays + 3 sick days
🏢 About the RoleWe're looking for a mid/senior Data Engineer to join a fast-growing tech company that builds data products for online retail brands.The focus is pipelines, transformations, and data quality, with no data science or ML work. Connecting to an API is the easy part. The real job is figuring out why a new vendor's data looks wrong before modeling it.A great fit for a curious, independent "data detective" who ships fast and works comfortably with AI coding agents.
🔍 ResponsibilitiesBuild ingestion pipelines from third-party APIs and vendor systemsInvestigate new data sources: spot nulls, inconsistent types, and odd behaviors, and find the root causeModel and test data in dbt so it's clean and trustworthyDirect AI coding agents and critically review the code they produceShip new integrations within tight customer timelines and document each source's quirks
🛠️ Requirements5+ years of experience in data engineeringStrong Python and SQLHands-on experience with dbtPipelines built from third-party APIs, ideally with dlt (Fivetran or Airbyte also relevant)Experience untangling messy, poorly documented source dataDay-to-day use of AI coding agents
✨ Nice to HaveE-commerce or DTC data (store platforms, ad platforms, marketing tools)DuckDB or MotherDuckTemporal or similar orchestration tools
🧠 Who You AreCurious and patient: you dig until you understand why the data looks wrongIndependent: you pick up new systems quickly, without hand-holdingComfortable with startup pace, without compromising on qualityA clear communicator about data issues and their impact
🎓 EducationDegree in Computer Science, Engineering, or a related field (or equivalent experience)Strong spoken and written English