Sr Data Engineer

Experience Summary

6–8 years of Data Engineer specialized in building document and knowledge-oriented data pipelines for regulatory/compliance domains, with strong capabilities in structured transformations, knowledge graphs, and containerized platform integration.

Core Responsibilities / Focus

• Build and operate data ingestion and transformation pipelines for legal/regulatory content
• Normalize and transform heterogeneous source formats (e.g., XML/HTML/structured exports) using tools such as XSLT
• Implement pipelines for embeddings generation, indexing, and enrichment for downstream AI/RAG systems
• Design and manage RDF-based knowledge representations and SPARQL-accessible datasets
• Integrate storage and processing components across containerized/cloud environments
• Support event-driven or integration-heavy workflows (e.g., via Apache Camel, message brokers)
• Ensure reproducibility, maintainability, and operational handover of data pipelines

Core Skills (Must-Have)

• Python
• Docker / Docker Compose
• Kubernetes
• Knowledge Graphs (RDF)
• SPARQL
• XSLT
• /Java
• Embeddings pipelines / vector preparation
• Azure Storage (or equivalent cloud storage services)
• Apache Camel
• Git

Preferred / Nice-to-Have

• Docling (or similar Document conversion)
• Cloud Events
• Kafka (or other message brokers)
• Event-based systems / event-driven architecture
• Dev Containers
• Git Ops
• Documentation practices

Domain Advantage

Experience processing legal/regulatory source documents and preserving semantic structure / provenance

Familiarity with content domains such as EU regulation, privacy, ESG, and compliance frameworks

Educational qualification:

BE/B.Tech or Equivalent Degree

Experience :

6-8 Years

Mandatory/requires Skills :

Strong hands-on expertise in Python, Docker / Docker Compose, Kubernetes, Knowledge Graphs,Java (RDF),SPARQL,XSLT,Embeddings pipelines / vector preparation, Azure Storage (or equivalent cloud storage services),

Apache Camel,Git

Preferred Skills :