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)

• CloudEvents

• Kafka (or other message brokers)

• Event-based systems / event-driven architecture

• Dev Containers

• GitOps

• 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 :