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Software Engineer

apartmentNeutron Pte Ltd placeSingapore calendar_month 
Key Responsibilities
  • Architect and implement high-throughput data ingestion pipelines for telemetry and sensor data.
  • Build backend services and APIs for data insertion, retrieval, configuration, and operational platform functions.
  • Design low-latency RESTful, gRPC, or equivalent APIs for high-frequency time-series workloads.
  • Implement streaming or near-real-time quality control logic, including anomaly detection and configurable validation rules.
  • Design non-proprietary time-series schemas that support efficient storage, retrieval, governance, and future extensibility.
  • Support access control, data governance, auditability, and secure integration patterns.
  • Collaborate with IoT/network engineers to define ingestion contracts, payload formats, protocol boundaries, and error handling.
  • Work with stakeholders to validate performance, stability, and reliability against agreed platform requirements.
  • Contribute to system documentation, deployment notes, API specifications, and operational handover materials.
Required Skills and Experience
  • Strong backend engineering experience with high-throughput, cloud-based data platforms.
  • Experience designing and operating data ingestion pipelines for streaming, telemetry, sensor, IoT, or time-series data.
  • Proficiency in at least one modern backend language such as Python, Java, Go, Node.js, or similar.
  • Experience designing production-grade APIs, including REST, gRPC, or equivalent programmatic interfaces.
  • Familiarity with time-series databases, relational databases, data lakes, or scalable storage systems.
  • Understanding of performance tuning, data partitioning, batching, backpressure, observability, and reliability patterns.
  • Ability to work across data engineering, backend development, and platform integration concerns.
Good to Have
  • Experience with cloud services, containerized deployments, CI/CD, infrastructure-as-code, or managed streaming technologies.
  • Familiarity with data quality frameworks, rules engines, or anomaly detection for operational data.
  • Experience with environmental, geospatial, industrial IoT, or mission-critical data systems.
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