Data Engineer - Python & ML

We are looking for an experienced Data Engineer to join an international technology project focused on building and evolving a data-processing platform that handles structured and unstructured information from multiple sources.

You will work on multi-format data ingestion, data normalization, entity reconciliation, relational data modeling and classification workflows, helping transform heterogeneous information into reliable and standardized datasets.

🔎 What will you work on?

• Build and maintain Python pipelines for processing Excel, PDF and XML sources.
• Extract structured records and specification lists from Excel using pandas and openpyxl.
• Process unstructured requirements from PDF documents using pypdf.
• Parse XML documents securely using defusedxml, including protection against XXE vulnerabilities.
• Map raw source fields into a canonical data model.
• Normalize categorical and hierarchical attributes such as product line, variant, region and language.
• Reconcile inconsistent terminology and entity names using fuzzy and approximate matching.
• Maintain relational data models using PostgreSQL and SQLAlchemy ORM.
• Support and improve existing scikit-learn classification workflows.
• Retrain and evaluate models and adjust decision thresholds according to precision, recall and F1 requirements.

🛠️ What are we looking for?

• Strong professional experience with Python.
• Experience with Django for backend development and data-driven applications.
• Experience working with pandas and openpyxl.
• Experience processing or extracting information from PDF and XML documents.
• Knowledge of data normalization, schema mapping and canonical data models.
• Experience with fuzzy matching techniques, ideally using rapidfuzz.
• Strong knowledge of SQL and PostgreSQL.
• Experience with SQLAlchemy ORM.
• Practical experience with scikit-learn classification workflows.
• Understanding of classification metrics such as precision, recall and F1-score.
• Experience with algorithms such as KNN, Random Forest or SVM.

➕ Nice to have

• Experience with AWS Aurora or other cloud-managed relational databases.
• Experience designing data ingestion or ETL/ELT pipelines.
• Experience working with heterogeneous datasets and complex source-data reconciliation.
• Knowledge of model threshold tuning and classification performance optimization.

💻 Technology Stack

Python · pandas · openpyxl · pypdf · defusedxml · rapidfuzz · PostgreSQL · SQLAlchemy · scikit-learn · KNN · Random Forest · SVM · AWS Aurora

If you enjoy solving complex data-processing problems and working at the intersection of Data Engineering, Data Quality and Machine Learning, we would love to hear from you.

📩 Apply or contact us to learn more about the project.