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Senior Data Engineer – Microsoft Fabric
Expleo Group. Design and develop scalable data ingestion pipelines for PDFs, Excel files, CSVs, and other structured/unstructured financial documents.
Tech Stack
Tools & technologiesETLNumpyPandasPySparkPythonSQL
About the role
Key responsibilities & impact- Design and develop scalable data ingestion pipelines for PDFs, Excel files, CSVs, and other structured/unstructured financial documents.
- Build normalization and transformation workflows to standardize messy financial and billing data.
- Develop reconciliation and validation engines to compare invoices against contract terms, pricing schedules, SLAs, and billing rules.
- Implement ETL/ELT pipelines using Microsoft Fabric components including Data Factory, Lakehouse, Notebooks, and Pipelines.
- Build data quality checks, exception handling frameworks, and audit mechanisms for financial accuracy.
- Create reusable Python-based processing modules for document parsing, data extraction, validation, and reconciliation.
- Work with OCR/document extraction tools and integrate outputs into downstream validation systems.
- Optimize data processing performance for high-volume financial records.
- Collaborate with product, business, and engineering teams to understand reconciliation rules and billing logic.
- Ensure security, governance, and compliance standards are followed for financial data handling.
- Support deployment, monitoring, troubleshooting, and continuous improvement of data workflows.
Requirements
What you’ll need- 7+ years of experience in Data Engineering and backend data processing systems.
- Minimum 1–2 years of hands-on experience with Microsoft Fabric.
- Strong proficiency in Python and data processing libraries such as: Pandas, PySpark, NumPy, OpenPyXL, PDF processing libraries (PyPDF2, pdfplumber, Camelot, Tabula, etc.)
- Experience building ETL/ELT pipelines and data transformation workflows.
- Strong experience with Microsoft Fabric services: Fabric, Data Factory, Lakehouse, Notebooks, Pipelines, OneLake
- Experience handling semi-structured and unstructured data sources.
- Strong SQL skills and data modeling knowledge.
- Experience implementing business rules, reconciliation logic, and data validation frameworks.
- Familiarity with REST APIs and external system integrations.
Benefits
Comp & perks- Health insurance
- 401(k) matching
- Flexible work arrangements
- Professional development opportunities
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data ingestiondata normalizationdata transformationETLELTPythonSQLdata modelingdata validationdata processing
Soft Skills
collaborationcommunicationtroubleshootingcontinuous improvement