Python Developer (Data Extraction)

Hiretop; United States; Teletrabalho; USD 110 000 - 165 000; Tempo integral

Resumo da oferta

Hiretop is seeking a highly detail-oriented Python Developer to join a technology company focused on extracting and structuring data from public online sources. You will build Python-based data extraction pipelines and ensure data quality across large volumes.

You will work with semi-structured and unstructured documents such as PDFs and OCR outputs, implement parsing and validation logic, and write automated tests with Pytest to guarantee accuracy.

Qualificações

• 4+ years of professional Python development experience.
• Experience with Python-based data extraction and ETL.
• Strong English communication (B2+).
• Hands-on with semi-structured or unstructured data (PDFs, scanned documents, OCR outputs).
• Experience writing tests with Pytest.

Responsabilidades

• Develop and maintain Python-based data extraction pipelines for processing large volumes of documents.
• Write Python code to extract structured data from scanned and semi-structured documents.
• Implement data parsing, normalization, and validation logic.
• Handle thousands of documents in varying formats and scan qualities.
• Improve and optimize existing extraction algorithms and workflows.
• Create automated tests with Pytest to ensure extraction accuracy.
• Develop validation logic and test cases to maintain data quality.
• Collaborate with team to improve document processing and data extraction approaches.

Conhecimentos

Python

Pytest

AWS Lambda

Step Functions

Data validation

Data quality checks

Analytical problem-solving

English (B2+)

Semi-structured data

OCR outputs

Ferramentas

PDF processing tools

OCR pipelines

Descrição da oferta de emprego

We’re looking for ahighly detail-oriented Python Developertojoin the team ofour client— atechnology company focused onextracting and structuring large volumes ofinformation from publicly available online resources.

The company works withbig data pipelines that selectively collect information from various public sources. This may involve web scraping, document processing, orintegrations with available data interfaces.

The core ofthe work revolves aroundcontinuously extracting and structuring large volumes ofdatafrom diverse sources and formats.

Responsibilities

• Develop and maintainPython-based data extraction pipelinesfor processing large volumes ofdocuments
• Write Python code toextract structured data from scanned and semi-structured documents, mostly containing financial information
• Implement logic fordata parsing, normalization, and validation
• Handle thousands ofdocuments with different formats and varying scan quality
• Improve and optimize existing data extraction algorithms and workflows
• Write and maintain automated tests using Pytest toensure extraction accuracy
• Create validation logic and test cases tomaintain high data quality standards
• Collaborate with the team to improve document processing and data extraction approaches

What this role isNOT

• Not focused onbuilding APIs orAPI integrations
• Not atypical backend product development position

This role isfocused specifically ondata extraction, processing, and validation.

What candidates need tobesuccessful

• 4+years ofprofessional experience withPython
• Level ofEnglish— B2+
• Strong experience writing clean, maintainable, and testable Python code
• Hands-on experience working with semi-structured orunstructured data (e.g., PDFs, scanned documents, OCR outputs)
• Strong skills indata validation, data quality checks, and analytical problem-solving
• Experience designing test cases and automated tests usingPytest
• Ability towork with large volumes ofdata and complex document formats
• Exceptional attention todetail and accuracy, especially when working with financial orsensitive data
• Experience debugging and improving data extraction logic and parsing algorithms
• Familiarity withAWS Lambda and Step Functions
• Experience working with document processing orOCR pipelines
• Experience building data processing pipelines orETL workflows
• Familiarity with large-scale data processing orbig data environments