Database Specialist

About Gradera — Digital Twin & Physical AI Platform 

At Gradera, we are building a next-generation Digital Twin and Physical AI platform that enables enterprises to model, simulate, and optimize complex real-world systems. Our work brings together strategy, architecture, data, simulation, and experience design to power decision-making across large-scale operational environments such as manufacturing, logistics, and supply chain networks. 

 

This platform-led initiative applies AI-native execution, advanced simulation, and governed orchestration to help organizations test scenarios, predict outcomes, and continuously improve performance. We operate with an enterprise-first mindset prioritizing reliability, transparency, and measurable business impact as we build intelligent systems that scale beyond a single industry or use case. 

Database Specialist 

Overview 

We are seeking an experienced Database Specialist with deep expertise in graph databases and time-series data stores to own the full lifecycle — from design to operations — of the data persistence layer for our digital twin platforms. You will be responsible for data modeling, schema design, query optimization, as well as DBA functions including installation, security, replication, backup/recovery, and incident response. This role is critical to ensuring reliable, performant, and secure databases that power simulation and operational intelligence. 

Our core database stack includes: 

Graph Database 

• Neo4j for network topology modeling and relationship graphs 

• Cypher for graph queries and traversals 

• Graph algorithms (pathfinding, centrality, community detection) 

Time-Series Database 

• TimescaleDB for high-volume operational and temporal data 

• Continuous aggregates and retention policies 

• Time-series indexing and compression 

Analytics & Governance 

• Databricks SQL for analytical queries 

• Unity Catalog for metadata management and governance 

• Spatial data indexing and geospatial queries 
  
  

Key Responsibilities 

• Design and implement Neo4j graph models for network topology, assets, and dependencies 

• Develop and optimize Cypher queries for complex traversals and real-time lookups 

• Architect TimescaleDB schemas for high-volume time-series data with partitioning and retention 

• Implement graph algorithms for pathfinding, connectivity, and network optimization 

• Tune database performance via indexing, query optimization, and schema design 

• Install, configure, and maintain Neo4j and TimescaleDB across environments 

• Manage database security, access control, encryption, and compliance logging 

• Configure replication, clustering, failover, and execute upgrades/migrations 

• Establish monitoring, alerting, capacity planning, and incident response 

• Integrate with Databricks lakehouse, support Unity Catalog, and document standards/procedures 
  
  

Preferred Qualifications 

• 8+ years of database engineering/DBA experience, with 4+ years in graph or time-series databases 

• Track record of designing and operating production-grade Neo4j or TimescaleDB deployments at scale 

• Experience with graph algorithm libraries (Neo4j GDS, NetworkX) 

• Experience managing databases in enterprise environments with strict SLAs and compliance requirements 

• Experience working in agile, cross-functional teams 
  
  

Highly Desirable 

• Experience with database design and operations for digital twin or simulation platforms 

• Familiarity with network topology modeling (infrastructure, logistics, utilities, or similar domains) 

• Experience with temporal graph patterns (versioned relationships, time-varying properties) 

• Exposure to hybrid query patterns combining graph traversals with time-series analytics 

• Experience with database migration and schema evolution strategies at scale 

• Neo4j Certified Professional or equivalent certification 

• Exposure to industrial domains such as Manufacturing, Logistics, or Transportation is a plus 

 

Location: Hyderabad, Telangana 
Department: Engineering 
Employment Type: Full-Time