Senior Data Engineer (4103)

Ciklum

Що робити

Data Pipeline Architecture: Build and optimize high-throughput data processing pipelines linking static code analysis outputs, graph databases, vector indexes, and LLM orchestration layers
Knowledge Graph Engineering: Design and maintain Neo4j graph schemas to map code dependencies, function calls, and module hierarchies across 400K+ LOC
AST Integration: Integrate Abstract Syntax Tree (AST) parser outputs (Tree-sitter) into downstream knowledge graphs and vector embeddings (Qdrant)
Data Lineage & Integrity: Implement bidirectional cross-reference tracking and graph snapshot versioning to ensure data consistency across batch documentation runs
Pipeline Testing & Monitoring: Establish data validation protocols and automated testing for pipeline health, throughput, and state persistence

Professional Experience: 5+ years of Data Engineering experience building complex, production-grade data pipelines and ETL/ELT workflows
Domain Specialization (Must cover at least ONE key domain):
Option 1 (Static Analysis Focus): Hands-on experience with Abstract Syntax Tree (AST) parsing, static code analysis (e.g., Tree-sitter, language grammars), and code structure modeling
Option 2 (Knowledge Graph Focus): Direct experience with graph database design and optimization (Neo4j/Cypher), documentation processing pipelines, and vector search integration (Qdrant)
Core Technical Stack: High proficiency in Python, graph query languages, vector storage, and modern data engineering toolkits