Sourcebae
Website:
sourcebae.com
Job details:
Job Description: IoT Consultant (Mid-Level)
Experience Level: 3–5 Years
Location: Remote
Skill to Evaluate
IoT-Architecture-Design,-Communication-Protocols-(MQTT/CoAP/LoRaWAN),-Cloud-Platform-Integration-(AWS/Azure-IoT),-Embedded-Programming-(Python/C++),-IoT-Security-&-Device-Management
Role Overview
We are looking for a proactive and technically-grounded IoT Consultant to bridge the gap between complex hardware ecosystems and business intelligence. With 3 to 5 years of experience, you’ve moved past the "tinkering" phase and understand how to scale IoT deployments from prototype to production. You will be responsible for designing end-to-end IoT architectures, selecting the right connectivity protocols, and ensuring seamless data integration into cloud platforms.
Key Responsibilities
Solution Architecture: Design and implement end-to-end IoT solutions, including edge device selection, gateway configuration, and cloud connectivity.
Protocol Expertise: Implement and optimize communication protocols such as MQTT, CoAP, HTTP/REST, and LoRaWAN based on specific project constraints (latency, power, bandwidth).
Cloud Integration: Develop and manage IoT hubs and data pipelines on platforms like AWS IoT Core, Azure IoT Hub, or Google Cloud IoT.
Security First: Implement robust security measures, including device identity management, X.509 certificate handling, and secure boot processes.
Stakeholder Liaison: Translate technical "sensor-speak" into actionable business insights for clients and internal leadership.
Troubleshooting: Conduct root-cause analysis for connectivity drops, latency issues, and hardware-software interface bugs.
Technical Requirements
Foundational Knowledge: Deep understanding of the IoT World Forum Reference Model (7-Layer) or similar architectural frameworks.
Programming: Proficiency in Python, C/C++, or Node.js for edge logic and cloud functions.
Hardware Familiarity: Experience working with microcontrollers (ESP32, ARM Cortex-M) and Single Board Computers (Raspberry Pi, Jetson Nano).
Data Management: Knowledge of Time-Series Databases (e.g., InfluxDB, TimescaleDB) and real-time data processing.
Connectivity: Hands-on experience with wireless standards (Wi-Fi, BLE, Zigbee) and cellular IoT (NB-IoT/LTE-M).
Preferred Qualifications
Edge AI: Experience deploying basic Machine Learning models at the edge (TinyML).
Certifications: AWS Certified Data Engineer or Azure IoT Developer Specialty.
DevOps for IoT: Familiarity with "Over-the-Air" (OTA) update strategies and containerization (Docker) at the edge.
Click on Apply to know more.