Description

You will build and operate data ingestion and transformation pipelines for legal and regulatory content processing.

This role is on-site.

Responsibilities

• Normalize and transform heterogeneous source formats (XML, HTML, structured exports) using XSLT tools.
• Implement pipelines for embeddings generation, indexing, and enrichment for downstream AI and RAG systems.
• Design and manage RDF-based knowledge representations and maintain SPARQL-accessible datasets.
• Integrate storage and processing components across containerized and cloud environments.
• Support event-driven workflows using Apache Camel and message brokers.

Required Skills

• 5+ years of experience as a Data Engineer building document and knowledge-oriented pipelines.
• Proficiency in Python and Java.
• Experience with Docker and Kubernetes.
• Knowledge of SPARQL, XSLT, and Embedding generation.
• Familiarity with Azure Storage.
• Experience integrating components using Apache Camel.
• Strong capability in structured transformations and knowledge graphs.

Preferred Skills

• Experience with regulatory domain data processing.

Key Skills

Education

Any Graduate