A fast-growing deep-tech company operating in the advanced sensing, AI, and real-time analytics space is seeking a skilled Data Engineer to help build the next generation of data and ML infrastructure powering mission-critical intelligent systems.

This role sits at the intersection of high-frequency sensor data, machine learning infrastructure, cloud platforms, and real-world edge deployments. You will work closely with engineering and ML teams to build scalable data systems that transform complex telemetry into actionable intelligence.

The Role As a Data Engineer, you will design and maintain robust data pipelines and infrastructure supporting large-scale sensor ingestion, analytics, and machine learning workflows.
You’ll contribute across the full data lifecycle — from edge-to-cloud ingestion through training data preparation and operational analytics — within a highly collaborative, engineering-led environment.

Key Responsibilities
  • Design and implement scalable data pipelines for ingesting, processing, and delivering high-frequency sensor and telemetry data
  • Build architectures supporting both real-time stream processing and large-scale batch analytics
  • Own core data platform infrastructure including time-series databases and object storage systems
  • Develop ML data pipelines including:
    • dataset preparation
    • labeling workflows
    • feature stores
    • version-controlled training datasets
  • Define and enforce data schemas, contracts, and quality standards across distributed data sources
  • Design cloud-side data systems optimized for bandwidth-constrained edge environments
  • Build internal dashboards, APIs, and analytics tooling to support engineering and product teams
  • Support field data collection activities including deployment and management of sensor datasets
  • Collaborate cross-functionally with Embedded, RF, Signal Processing, and ML Engineering teams
  • Monitor and optimize pipeline performance to ensure reliable low-latency data delivery
Required Experience
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related discipline
  • 3 years of experience in Data Engineering, ML Infrastructure, or backend data systems
  • Hands-on experience with data processing technologies such as Kafka, Spark, Flink, or similar frameworks
  • Experience working with time-series or event-driven data at scale
  • Strong understanding of data modeling, schema management, and production data quality practices
  • Experience with AWS (or similar cloud platforms) and infrastructure-as-code methodologies
  • Familiarity with CI/CD pipelines and automated testing for data workflows
  • Strong English communication skills
Preferred Experience
  • Background working with IoT, embedded systems, or hardware-generated data
  • Understanding of edge computing and on-device data reduction strategies
  • Experience supporting ML feature engineering and training data infrastructure
  • Familiarity with event-driven architectures and real-time distributed systems
  • Exposure to regulated, security-sensitive, or mission-critical environments
  • Startup or high-growth company experience
Why Join?
  • Work on cutting-edge AI and sensing technologies with real-world impact
  • Solve complex engineering challenges involving real-time data and intelligent systems
  • Collaborate with highly technical multidisciplinary teams
  • Influence the architecture of next-generation ML and analytics platforms
  • Join a fast-moving, innovation-driven environment with significant growth potential
For a confidential discussion regarding this opportunity, please apply directly.