Senior Data & Document Ingestion Engineer
G
Gramian ConsultancyFinancial Services, IT
Poland. Czechia. Bosnia and Herzegovina. Croatia. Romania. FranceContractSenior
Salary not disclosed
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Job Details
- Languages
- Fluent English is required.
- Experience
- 5–10 years of professional data engineering or backend/data-platform experience
- Required Skills
- AWSPythonSQLGitAzureData engineeringCI/CDDatabricks
Requirements
- 5–10 years of professional data engineering or backend/data-platform experience.
- Strong hands-on experience with Python and SQL.
- Proven experience building data ingestion and document-processing pipelines.
- Hands-on experience processing unstructured documents such as PDF, Word, Excel, PPT, scans, or emails.
- Experience with OCR/document extraction tools such as AWS Textract or equivalent.
- Professional experience building data-processing pipelines on public cloud platforms.
- Experience with AWS services such as S3, Step Functions, and CloudWatch, or comparable cloud services.
- Strong development practices including Git, CI/CD, and automated testing.
- Fluent English proficiency.
- Experience with Azure, AWS, or Databricks in enterprise data environments (preferred).
- Experience with vector databases, embeddings, or RAG architectures (preferred).
- Experience designing connectors to SharePoint, email, or other enterprise content systems (preferred).
Responsibilities
- Design and build scalable document ingestion pipelines for PDFs, scans, emails, and office documents.
- Integrate and optimize OCR and document extraction technologies for high-accuracy text and layout extraction.
- Build workflows for text cleaning, normalization, semantic chunking, and metadata tagging.
- Process unstructured formats including PDF, Word, Excel, and PowerPoint.
- Develop connectors for enterprise sources such as SharePoint and email systems.
- Design data schemas and retrieval mechanisms for downstream AI and RAG use cases.
- Build validation and monitoring loops to detect low-confidence OCR or extraction results.
- Ensure ingestion pipelines meet enterprise security, reliability, and latency requirements.
- Implement logging, testing, and operational monitoring across data-processing workflows.
- Apply Git, CI/CD, and software-engineering best practices to pipeline development.
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