Lead 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. 

Lead Data Engineer 

Overview 

We are seeking a hands-on, collaborative Lead Data Engineer to drive the technical direction, architecture, and delivery of our data foundation for digital twin and AI-powered enterprise platforms. As Lead Data Engineer, you will provide technical leadership and guidance to the data engineering team, ensuring the delivery of robust, scalable, high-performance data pipelines that power real-time operational intelligence and simulation-ready data products. This role partners closely with data architects, simulation engineers, ML engineers, and platform teams. 

Our core data platform stack includes: 

Data Platform & Lakehouse 

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

• Delta Lake and Apache Iceberg for lakehouse architecture and ACID-compliant data lakes 

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

Stream & Event Processing 

• Apache Kafka for real-time event ingestion and streaming 

• 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 

• TimescaleDB for time-series operational data 

• Python, Scala, and SQL for data transformation and orchestration 
  
  

Data Quality & Governance 

• Great Expectations and Delta Live Tables expectations for data validation 

• Unity Catalog for metadata management and compliance 
  
  

Key Responsibilities 

• Provide technical leadership, mentorship, and guidance to the data engineering team 

• Lead the design, implementation, and evolution of data pipelines, lakehouse architecture, and real-time event processing systems 

• Architect and build data foundations that serve digital twin platforms, AI/ML workloads, and operational analytics 

• Ensure delivery of high-quality, well-governed, and performant data products using Unity Catalog and Delta Lake 

• Design and implement graph data integration patterns for network topology and relationship modeling 

• Drive adoption of DataOps best practices, including CI/CD for data pipelines, automated testing, and monitoring 

• Champion data hygiene, quality frameworks, and observability across the data estate 

• Oversee real-time data ingestion from diverse operational systems and IoT sources 

• Guide the use of modern data engineering tools, architectural patterns, and emerging technologies 

• Own the implementation and quality of data lineage, cataloging, and governance to enable trust and compliance 

• Collaborate with simulation engineers and ML teams to deliver simulation-ready and feature-engineered datasets 

• Ensure engineering rigor, code quality, and documentation standards are met across the data stack 

• Facilitate clear communication, knowledge sharing, and effective documentation within the team 

• Support team growth through coaching, feedback, and skills development 

• Drive development efficiency and alignment with product team priorities through clear prioritization frameworks and delivery metrics 
  
  

Preferred Qualifications 

• 10+ years of hands-on data engineering experience, with 4+ years in a technical leadership role 

• Track record of architecting and delivering scalable, production-grade data platforms 

• Experience with modern DataOps practices (CI/CD for data, automated testing, pipeline monitoring) 

• Demonstrated ability to mentor and grow data engineers 

• Experience working in cross-functional, agile teams 
  
  

Highly Desirable 

• Experience building data foundations for digital twin or simulation platforms 

• Familiarity with OpenUSD data pipelines or FMI/FMU data integration 

• Experience with physics-informed or operational ML feature engineering 

• Track record of delivering data platforms with sub-second latency for real-time operational use cases 

• Experience thriving in fast-paced, ambiguous environments and balancing rapid delivery with technical excellence 

• Experience leading or 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