Data Engineer

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. 

Data Engineer  

Overview 

We are seeking skilled Data Engineers to join our Data & Digital Twin Foundation team. You will design, build, and maintain data pipelines that power digital twin platforms, real-time operational systems, and AI/ML workloads. Working closely with data architects, simulation engineers, and ML teams, you will transform raw operational data into high-quality, governed datasets that drive intelligent decision-making. 

Our core data platform stack includes: 

Data Platform & Lakehouse 

• Databricks (PySpark, Databricks SQL) for unified analytics and data engineering 

• Delta Lake for ACID-compliant lakehouse architecture 

• Unity Catalog for data governance, lineage, and access control 

Stream & Event Processing 

• Apache Kafka for real-time event ingestion 

• Structured Streaming for continuous data processing 

• Delta Live Tables for declarative, quality-enforced pipelines 

Specialized Data Stores 

• Neo4j for graph data modeling and network topology 

• Python and SQL for data transformation 

Data Quality 

• Delta Live Tables expectations for data validation 

• Data profiling and anomaly detection 
  
  

Key Responsibilities 

• Design, develop, and maintain scalable data pipelines using Databricks, PySpark, and Delta Lake 

• Build real-time and batch data ingestion pipelines from diverse operational systems 

• Implement data transformations that serve digital twin platforms and operational analytics 

• Develop and maintain graph data models in Neo4j for network topology and relationship modeling 

• Integrate Kafka event streams with Databricks for real-time operational state updates 

• Implement data quality checks using Delta Live Tables expectations 

• Ensure data governance compliance through Unity Catalog (lineage, access control, metadata) 

• Optimize pipeline performance, reliability, and cost efficiency 

• Write clean, well-documented, and testable code following engineering best practices 

• Collaborate with ML engineers to deliver feature-engineered datasets 

• Participate in code reviews, knowledge sharing, and continuous improvement initiatives 

• Support production data systems through monitoring, troubleshooting, and incident resolution 
  
  

Preferred Qualifications 

• 7+ years of hands-on data engineering experience 

• Track record of building and maintaining production-grade data pipelines 

• Experience with Delta Live Tables for declarative pipeline development 

• Experience working in agile, cross-functional teams 

• Familiarity with time-series data patterns and operational data modeling 
  
  

Highly Desirable 

• Experience building data pipelines for digital twin or simulation platforms 

• Familiarity with operational state modeling for real-time systems 

• Exposure to physics-informed or time-series ML feature engineering 

• Experience working with distributed, multidisciplinary teams 

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

 

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