Data Engineer

Key Skills: ETL/ELT, RDF, OWL, SPARQL, Neo4j, AWS Neptune, ArangoDB, Python, SQL, Cypher, Semantic Modeling, Cloud Data Pipelines, Data Quality, Knowledge Graph, Graph Query Optimization, Semantic Search.

Roles and Responsibilities:

• Design and build advanced data pipelines for integrating structured and unstructured data into graph models.
• Develop and maintain semantic models using RDF, OWL, and SPARQL.
• Implement and optimize data pipelines on cloud platforms such as AWS, Azure, or GCP.
• Model real-world relationships through ontologies and hierarchical graph data structures.
• Work with graph databases such as Neo4j, AWS Neptune, ArangoDB for knowledge graph development.
• Collaborate with cross-functional teams including AI/ML and business analysts to support semantic search and analytics.
• Ensure data quality, security, and compliance throughout the pipeline lifecycle.
• Monitor, debug, and enhance performance of graph queries and data transformation workflows.
• Create clear documentation and communicate technical concepts to non-technical stakeholders.
• Participate in global team meetings and knowledge-sharing sessions to align on data standards and architectural practices.

Experience Requirement:

• 3-8 years of hands-on experience in ETL/ELT engineering and data integration.
• Experience working with graph databases such as Neo4j, AWS Neptune, or ArangoDB.
• Proven experience implementing knowledge graphs, including semantic modeling using RDF, OWL, and SPARQL.
• Strong Python and SQL programming skills, with proficiency in Cypher or other graph query languages.
• Experience designing and deploying pipelines on cloud platforms (AWS preferred).
• Track record of resolving complex data quality issues and optimizing pipeline performance.
• Previous collaboration with data scientists and product teams to implement graph-based analytics or semantic search features.

Education:  Any Graduation