Graph Database Engineer

Agivant; Pune District; Presencial; INR 1.200.000 - 2.400.000; Tempo integral

Resumo da vaga

Agivant Technologies India Private Limited is seeking a Graph Database Engineer with deep Neo4j expertise to design, build, and optimize scalable graph data solutions. You will craft high-performance graph infrastructures powering knowledge graphs and AI-driven apps, focusing on Cypher optimization, modeling, and robust administration.

You will collaborate with data, engineering, and AI teams to enable efficient data relationships at scale, ensuring data integrity and security across graph

Qualificações

• Strong hands-on experience with Neo4j in production environments.
• Proficiency in writing and optimizing Cypher queries for large-scale datasets.
• Solid understanding of graph data structures, relationships, and traversal techniques.
• Experience with indexing, query planning, and performance tuning in graph databases.
• Knowledge of database administration including backup, recovery, and clustering.
• Familiarity with integrating graph databases into application ecosystems via APIs or services.
• Experience working with large, complex datasets in distributed environments.
• Understanding of data modeling principles for knowledge graphs or connected data systems.

Responsabilidades

• Design and implement scalable graph database architectures using Neo4j.
• Develop, optimize, and maintain complex Cypher queries for high-performance data retrieval.
• Model complex datasets into efficient graph structures aligned with business use cases.
• Monitor and tune database performance, including indexing strategies and query execution plans.
• Manage database operations such as backups, recovery, clustering, and scaling.
• Collaborate with data scientists and AI teams to support knowledge graph and RAG-based applications.
• Ensure data integrity, consistency, and security across graph systems.
• Troubleshoot performance bottlenecks and implement improvements in query and schema design.
• Automate routine database maintenance and monitoring tasks.
• Document graph schemas, data flows, and operational procedures for internal stakeholders.

Conhecimentos

Neo4j

Cypher

Graph modeling

Performance tuning

DB administration

APIs integration

Distributed data

Ferramentas

REST APIs

Descrição da vaga

Agivant Technologies India Private Limited | Full time

Agivant is a new-age AI-First Digital and Cloud Engineering services company that drives Agility and Relevance for our client’s success.

Powered by cutting-edge technology solutions that enable new business models and revenue streams, we help our clients achieve their trajectory of growth.

Agility is a core muscle, an integral part of the fabric of a modern enterprise. To succeed in an ever-changing business environment, every modern organization needs to adapt and renew itself quickly. We help foster a more agile approach to business to reconfigure strategy, structure, and processes to achieve more growth and drive greater efficiencies.

Relevance is timeless and is the only way to survive and thrive.

The quest for relevance defines the exponential acceleration of humanity. This has presented us with a slew of opportunities, but also many unprecedented challenges. With technology-led innovation, we help our customers harness these opportunities and address myriad challenges.

Job Description

We are seeking a Graph Database Engineer with deep expertise in Neo4j to design, build, and optimize scalable graph data solutions. This role focuses on developing high-performance graph infrastructures that power knowledge graphs and AI-driven applications. The ideal candidate will bring strong hands-on experience with Cypher query optimization, graph data modeling, and database administration. You will work closely with data, engineering, and AI teams to enable efficient data relationships and insights at scale.

Key Responsibilities

• Design and implement scalable graph database architectures using Neo4j.
  
• Develop, optimize, and maintain complex Cypher queries for high-performance data retrieval.
  
• Model complex datasets into efficient graph structures aligned with business use cases.
  
• Monitor and tune database performance, including indexing strategies and query execution plans.
  
• Manage database operations such as backups, recovery, clustering, and scaling.
  
• Collaborate with data scientists and AI teams to support knowledge graph and RAG-based applications.
  
• Ensure data integrity, consistency, and security across graph systems.
  
• Troubleshoot performance bottlenecks and implement improvements in query and schema design.
  
• Automate routine database maintenance and monitoring tasks.
  
• Document graph schemas, data flows, and operational procedures for internal stakeholders.
  

Requirements

Required Qualifications

• Strong hands-on experience with Neo4j in production environments.
  
• Proficiency in writing and optimizing Cypher queries for large-scale datasets.
  
• Solid understanding of graph data structures, relationships, and traversal techniques.
  
• Experience with indexing, query planning, and performance tuning in graph databases.
  
• Knowledge of database administration including backup, recovery, and clustering.
  
• Familiarity with integrating graph databases into application ecosystems via APIs or services.
  
• Experience working with large, complex datasets in distributed environments.
  
• Understanding of data modeling principles for knowledge graphs or connected data systems.
  

Preferred Qualifications

• Experience with graph-based AI/ML use cases such as recommendation systems or fraud detection.
  
• Exposure to Neo4j Aura or other managed graph database services.
  
• Familiarity with ETL pipelines and data ingestion into graph databases.
  
• Experience working with cloud platforms (AWS, GCP, or Azure).
  
• Knowledge of other database systems (SQL/NoSQL) and data integration patterns.
  

Experience Requirements

• 3–6 years of experience in database engineering or backend development.
  
• At least 2+ years of hands-on experience with Neo4j or other graph databases.
  
• Proven experience working on data-intensive applications or graph-based systems.