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Data Engineer – Software & AI for Jet and Cryogenic Engines

Location: Pune, India (Hybrid Available)

Scope of Work

We are seeking a Data Engineer with strong software and AI fundamentals to work on digital thread systems that support high-fidelity data acquisition, analytics, and simulation pipelines across combat jet and cryogenic engine programs. The role involves designing robust data pipelines and real-time analytics systems to support engine health monitoring, performance tuning, and failure prediction models.

Nature of Work

  • Developing and maintaining data pipelines from sensors and simulation outputs
  • Managing high-volume time-series data from testbeds and digital twins
  • Structuring data lakes and integrating with simulation engines and digital twins
  • Designing machine learning-ready datasets from thermodynamic and structural telemetry
  • Collaborating with CFD/thermal/structural analysts to contextualize data
  • Supporting FADEC and control algorithm teams with data-backed insights
  • Enabling closed-loop feedback mechanisms for predictive diagnostics
  • Deploying cloud-native or edge-ready data management solutions (e.g., Kubernetes, Kafka, Redis)

Job Requirements

  • B.E./B.Tech or M.E./M.Tech in Computer Science, Data Engineering, or allied discipline
  • 2–5 years of experience in building robust data pipelines, preferably in real-time systems
  • Proficiency in Python, SQL, and distributed data frameworks (Apache Spark, Kafka, etc.)
  • Understanding of sensor networks, edge computing, or digital twin environments is a plus
  • Hands-on with tools like TensorFlow, PyTorch, scikit-learn, and deployment environments like Docker or K8s
  • Experience with industrial protocols (CAN, MODBUS, OPC-UA) is an advantage
  • Strong version control (Git), CI/CD workflow familiarity
  • Good technical writing and data visualization abilities

Eligibility

  • Indian nationals or eligible to work in India
  • Exposure to aerospace, defense, or cryogenic domains is highly desirable
  • Open to candidates from research institutions, startups, or industry with a strong data engineering portfolio