Senior AI Data Engineer - RAG & Retrieval Architect

Billennium; Warszawa; On-site; PLN 180,000 - 280,000; Full time

Benefits offered by this job

Udemy for Business

Private medical care

Multisport card

Team-building events

Welcome pack

Job summary

Billennium is hiring a Senior AI Data Engineer / Data Scientist to transform unstructured enterprise data into AI-ready assets. You will own the data lifecycle for AI use cases—from discovery and cleaning to ingestion, retrieval optimization and continuous refresh.

You’ll work with SharePoint content, PDFs, Office files, wikis and data lakes to enable RAG systems and AI copilots. You will collaborate with AI Engineers, Architects and business stakeholders to ensure data quality, scalability and

Qualifications

• 5+ years of professional experience in Data Engineering, Applied Data Science, Analytics Engineering or related field.
• Proven experience owning production‑grade data pipelines.
• Strong Python skills for data processing, parsing, cleaning, normalization and pipeline development.
• Hands‑on experience with unstructured enterprise data (documents, PDFs, Office files, wikis).
• Experience preparing data for retrieval, NLP or RAG-based use cases, including embeddings and corpus management.

Responsibilities

• Lead enterprise data discovery and cleanup for AI use cases.
• Build and maintain ingestion pipelines for SharePoint and document repositories.
• Prepare data for retrieval and RAG applications, including chunking strategies and metadata enrichment.
• Define data quality gates and monitoring to ensure reliable AI knowledge.
• Maintain data lineage, governance and privacy requirements across pipelines.

Skills

Python

Data pipelines

Unstructured data handling

Data quality engineering

RAG and retrieval

Collaboration with AI teams

Tools

Postgres + pgvector

Langfuse

Job description

Billennium is hiring a Senior AI Data Engineer / Data Scientist to transform unstructured enterprise data into AI-ready assets. You will own the data lifecycle for AI use cases—from discovery and cleaning to ingestion, retrieval optimization and continuous refresh.

You’ll work with SharePoint content, PDFs, Office files, wikis and data lakes to enable RAG systems and AI copilots. You will collaborate with AI Engineers, Architects and business stakeholders to ensure data quality, scalability and