Data Engineer
- Full-time
- Mid level
- Remote (worldwide)
Remote Data Engineer at MacroCoderz: build the pipelines that feed AI systems - document ingestion, ETL, data syncs and vector indexing at scale.
Role at a glance
| Employment type | Full-time |
|---|---|
| Level | Mid level |
| Experience | 2+ years |
| Location | Remote (worldwide) |
| Team | Data and machine learning |
| Education | Degree in computer science or equivalent practical experience |
| Posted | 10 October 2026 |
About the role
An AI assistant that answers from stale or broken data is worse than no assistant. As a Data Engineer you build the pipelines that keep our systems fed: ingesting documents and records from client systems, cleaning and transforming them, and keeping vector indexes in sync as the source data changes.
What you will do
- Build batch and incremental ingestion pipelines from databases, APIs and file stores.
- Parse and clean documents - PDFs, HTML, spreadsheets - for retrieval.
- Keep vector indexes and metadata in sync with source systems.
- Model data in Postgres and warehouses for analytics and retrieval.
- Monitor pipeline health and data quality.
What we are looking for
- 2+ years of data engineering.
- Strong Python and SQL.
- Experience with an orchestration tool such as Airflow, Dagster or Prefect.
- Understands incremental loads, idempotency and schema changes.
Nice to have
- Has built ingestion for a RAG or search system.
- dbt, Spark or a cloud data warehouse.
- Document parsing tools such as Unstructured or Docling.
Skills and tools
- Python
- SQL
- ETL
- Airflow
- dbt
- PostgreSQL
- Data pipelines
- Vector indexing
Who this role suits
Data engineers and backend engineers who want to work on the data side of AI systems.
The work behind this role
Data Engineer: common questions
Yes. The Data Engineer role at MacroCoderz is fully remote and open to applicants worldwide. It is a full-time, mid level position.
2+ years (mid level). Education: Degree in computer science or equivalent practical experience. Who it suits: Data engineers and backend engineers who want to work on the data side of AI systems.
Because an AI assistant can only be as accurate as the data it retrieves. Data Engineers build the pipelines that ingest documents and records from client systems, clean them, and keep the vector index in sync when the source data changes.
Use the application form on this page. It asks for your contact details, city, LinkedIn profile, expected salary, how you heard about the role, a short description of two or three projects you have worked on, and your CV as a PDF or Word file. An engineer reviews every application and emails shortlisted applicants to arrange a call.