Data Engineer (Integrations & Data Quality) – REF 114 – 03

Purpose of the Role

We’re looking for a mid-to-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.

Duties and Responsibilities

• Build ingestion pipelines from third-party APIs and vendor systems.
• Investigate new data sources: spot nulls, inconsistent types, and odd behaviors, and find the root cause.
• Model and test data in dbt so it is clean and trustworthy.
• Direct AI coding agents and critically review the code they produce.
• Ship new integrations within tight customer timelines and document each source’s quirks.

Required Experience & Knowledge

Mandatory:

• 5+ years of experience in data engineering.
• Strong Python and SQL.
• Hands-on experience with dbt.
• Pipelines built from third-party APIs, ideally with dlt (Fivetran or Airbyte also relevant).
• Experience untangling messy, poorly documented source data.
• Day-to-day use of AI coding agents.

Nice to Have:

• E-commerce or DTC data (store platforms, ad platforms, marketing tools).
• DuckDB or MotherDuck.
• Temporal or similar orchestration tools.

Skills and Attributes

• Curious and patient: you dig until you understand why the data looks wrong.
• Independent: you pick up new systems quickly, without hand-holding.
• Comfortable with startup pace, without compromising on quality.
• Clear communicator about data issues and their impact.

Required Education & Qualifications

• Degree in Computer Science, Engineering, or a related field (or equivalent experience).
• Strong spoken and written English.