Senior Sofware Developer

Job Description

We are seeking a Senior IoT Platform Architect / Backend Engineer to design and scale a real-time IoT telemetry and control platform for millions of connected solar inverters and edge devices. The ideal candidate will architect and optimize a high-throughput, secure, and resilient data pipeline — from MQTT ingestion to time-series storage and analytics.

You’ll lead design and implementation of the end-to-end architecture , including :

MQTT Broker (EMQX / VerneMQ) clusters for device connectivity and secure telemetry ingestion.

Kafka-based streaming pipeline for durable, partitioned message processing at 100k–200k msg / sec scale.

Python (FastAPI / Django) consumers for validation, enrichment, and storage into TimescaleDB (Postgres) with Redis for low-latency caching.

Django REST Framework APIs and WebSocket gateways for real-time dashboards and control command flows.

Kubernetes-based deployment with auto scaling, Helm, and observability stack ( Prometheus, Grafana, ELK / Opensearch ).

Security-first design using mTLS, OAuth2 / OIDC (Keycloak), and Cloud KMS / HSM for secrets.

You’ll be responsible for capacity planning , data modeling , performance optimization , and ensuring high availability for millions of devices at sub-second latency. Experience with large-scale messaging systems, distributed databases, and time-series optimization is essential.

Requirements

You’ll lead design and implementation of the end-to-end architecture , including :

MQTT Broker (EMQX / VerneMQ) clusters for device connectivity and secure telemetry ingestion.

Kafka-based streaming pipeline for durable, partitioned message processing at 100k–200k msg / sec scale.

Python (FastAPI / Django) consumers for validation, enrichment, and storage into TimescaleDB (Postgres) with Redis for low-latency caching.

Django REST Framework APIs and WebSocket gateways for real-time dashboards and control command flows.

Kubernetes-based deployment with auto scaling, Helm, and observability stack ( Prometheus, Grafana, ELK / Opensearch ).

Security-first design using mTLS, OAuth2 / OIDC (Keycloak), and Cloud KMS / HSM for secrets.

You’ll be responsible for capacity planning , data modeling , performance optimization , and ensuring high availability for millions of devices at sub-second latency. Experience with large-scale messaging systems, distributed databases, and time-series optimization is essential.

Requirements

You’ll lead design and implementation of the end-to-end architecture, including : MQTT Broker (EMQX / VerneMQ) clusters for device connectivity and secure telemetry ingestion. Kafka-based streaming pipeline for durable, partitioned message processing at 100k–200k msg / sec scale. Python (FastAPI / Django) consumers for validation, enrichment, and storage into TimescaleDB (Postgres) with Redis for low-latency caching. Django REST Framework APIs and WebSocket gateways for real-time dashboards and control command flows. Kubernetes-based deployment with auto scaling, Helm, and observability stack (Prometheus, Grafana, ELK / Opensearch). Security-first design using mTLS, OAuth2 / OIDC (Keycloak), and Cloud KMS / HSM for secrets. You’ll be responsible for capacity planning, data modeling, performance optimization, and ensuring high availability for millions of devices at sub-second latency. Experience with large-scale messaging systems, distributed databases, and time-series optimization is essential.