
Senior Data Transformation Specialist
3 days ago
About the Role:
We are seeking a skilled Data Engineer to build robust pipelines that transform large, heterogeneous technical datasets into high-quality structured data.
The core focus is to extract, validate and improve mappings of structured attributes from unstructured/semi-structured documents (PDFs, images, CSVs, drawings, websites).
This role combines deterministic extraction techniques with cutting-edge automation to scale attribute mapping, quality assurance and structured comparisons across hundreds of datasets.
Key Responsibilities:
- Design and implement automated pipelines to extract structured attributes from unstructured documents using LLMs, regex, OCR and digitization tools.
- Apply machine learning algorithms to parse text, tables and graphics into structured formats.
- Build automated validation and anomaly detection checks to ensure high-quality data.
- Use RAG/document query frameworks to automatically surface additional attributes and integrate them into structured pipelines.
- Normalize heterogeneous data into structured outputs (CSV, SQL, JSON) for large-scale comparisons.
- Document workflows and maintain reusable extraction modules for scalability.
Qualifications:
- Strong Python skills with experience in data parsing and extraction libraries.
- Proven experience with LLM-based extraction/mapping pipelines.
- Experience handling messy/unstructured data (PDFs, images, JSON, XML).
- Knowledge of document query frameworks is a strong plus.
- Comfort with relational databases and structured data management.
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