Extracting Insights
1 week ago
We are seeking a Data Pipeline Architect to join our team.
Job Description
In this role, you will be responsible for designing and implementing robust data pipelines that extract structured attributes from unstructured/semi-structured documents (PDFs, images, CSVs, drawings, websites). You will leverage deterministic extraction techniques combined with cutting-edge LLM automation to scale attribute mapping, quality assurance, and structured comparisons across hundreds of datasets.
- We focus on developing scalable and maintainable pipelines using Python libraries such as BeautifulSoup, PyPDF2, Camelot, and OpenCV.
- You will apply regex, OCR, and digitization tools for parsing text, tables, and graphics into structured formats.
- Build automated validation and anomaly detection checks to ensure high-quality data.
- Use document query frameworks such as LangChain, LlamaIndex, and RAG to automatically surface additional attributes and integrate them into structured pipelines when recurring.
- Normalize heterogeneous data into structured outputs (CSV, SQL, JSON) for large-scale comparisons.
Required Skills and Qualifications
- Strong Python skills with hands-on 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 (PostgreSQL/MySQL) and structured data management.
Benefits
Our ideal candidate will have the opportunity to work on challenging projects, collaborate with a talented team, and grow professionally. We offer a competitive salary and benefits package.
Others
We value diversity and inclusion in the workplace and encourage applications from underrepresented groups.
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