Graph Data Engineer

We are seeking a highly motivated and experienced Data Engineer with a strong focus on Graph Databases to join our growing data team. In this role, you will be responsible for designing, building, and maintaining robust and scalable graph-based data solutions. You will work closely with data scientists, analysts, and application developers to leverage the power of graph databases for complex data analysis, knowledge representation, and real-time applications.

The candidate will have responsibilities across the following functions:

Graph Data Modelling and Design:

• Design and implement efficient and scalable graph data models using appropriate graph database technologies (e. g., Neo4j, Amazon Neptune, TigerGraph, etc. ).
• Translate business requirements into effective graph schemas and data structures.
• Optimise graph models for performance and query efficiency.

Graph Database Development and Management:

• Develop and maintain graph database instances, including installation, configuration, and performance tuning.
• Implement data ingestion and transformation pipelines to populate graph databases from various data sources.
• Develop and optimise Cypher, Gremlin, or other graph query languages for complex data retrieval and analysis.
• Implement data security and access control mechanisms for graph databases.
• Monitor and maintain the health of graph databases.

Data Integration and ETL/ELT:

• Design and implement ETL/ELT processes to integrate data from diverse sources into graph databases.
• Develop and maintain data pipelines using tools like Apache Kafka, Apache Airflow, or similar technologies.
• Ensure data quality and consistency throughout the data integration process.

Graph Analytics and Application Development:

• Collaborate with data scientists and analysts to develop graph-based analytics solutions.
• Develop and implement APIs and applications that leverage graph database capabilities.
• Develop and implement algorithms for graph traversals, community detection, and other graph analytics tasks.
• Participate in code reviews.

Secondary Responsibilities:

Performance Optimisation and Troubleshooting:

• Identify and resolve performance bottlenecks in graph database systems.
• Monitor and optimise query performance.
• Troubleshoot and resolve data-related issues.

Documentation and Best Practices:

• Document graph data models, data pipelines, and database configurations.
• Establish and enforce best practices for graph database development and management.
• Participate in code reviews.

Requirements:

• Technical Skills (Tools, Languages, Competencies): GraphDB, Amazon Neptune, Tiger Graph, Dgraph, etc. Spark, Apache Airflow, GPU Training/AWS/Azure, MongoDB, Postgres, Redis, Python, PySpark, Unix, semantic web technologies, REST APIs, containerization and orchestration, machine learning and graph analytics.
• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

Skills

airflow, dgraph, elt, etl, graphdb, kafka, neo4j, neptune, pyspark, python, spark, tigergraph