Data Modeling & ETL Development
Built ETL pipelines from Microsoft Fabric Data Lake into Neo4j
Design data models.
Transform raw structured and unstructured data into clean, well-modeled graph inputs (nodes, edges, metadata).
Create Source to Target Mappings (STMs) for ETL specifications.
Implement automated ingestion patterns, incremental (delta) updates, and streaming/CDC workflows.
Collaboration & Agile Development
Gather requirements, set targets, define interface specifications, and conduct design sessions.
Work closely with data consumers to ensure proper integration.
Adapt and learn in a fast-paced project environment.

Requirements

Strong SQL skills for ETL, data modeling, and performance tuning.
Experience with Neo4j
Proficiency in Python, especially for handling and flattening complex JSON structures.
Hands-on experience with Microsoft Fabric, Synapse, ADF, or similar cloud data stacks.
Knowledge of Cypher, APOC, and graph modeling.
Familiarity with GraphRAG, retrieval systems, or RAG hybrids.
Understanding of software engineering and testing practices within an Agile environment.
Experience with Data as Code; version control, small and regular commits, unit tests, CI/CD, packaging, familiarity with containerization tools such as Docker (must have) and Kubernetes (plus).
Excellent teamwork and communication skills.
Proficiency in English, with strong written and verbal communication skills.
Efficient, high-performance data pipelines for real-time and batch data processing.
Nice to have: Knowledge of cryptography and its application in enterprise data modeling in regulated industries (Banking, Finance, Ops)
Semantic models, ontologies, or knowledge engineering.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLETLdata modelingPythonNeo4jCypherAPOCData as CodeDockerKubernetes

Soft Skills

teamworkcommunicationadaptability