IoT Data Architect

We are seeking an experienced IoT Data Architect to design, build, and govern large-scale IoT data platforms that ingest, process, store, and analyze high-velocity sensor and device data. This is a senior, high-impact role responsible for defining end-to-end IoT data architecture, ensuring scalability, security, and reliability while enabling advanced analytics, real-time insights, and AI/ML use cases. The ideal candidate brings deep expertise in IoT ecosystems, data engineering, cloud platforms, streaming architectures, and enterprise data governance, and works closely with product, engineering, data science, and business teams.

Key Responsibilities :

IoT Data Architecture & Design :

- Define and own end-to-end IoT data architecture covering device ingestion, data pipelines, storage, processing, analytics, and visualization layers.

- Design scalable architectures for high-volume, high-velocity, and high-variety IoT data (time-series, telemetry, events, logs).

- Establish reference architectures, standards, and best practices for IoT data platforms.

Data Ingestion & Streaming :

- Architect and implement real-time and batch ingestion pipelines using MQTT, AMQP, HTTP, Kafka, Azure Event Hubs, AWS Kinesis, or similar technologies.

- Ensure reliable device-to-cloud communication, fault tolerance, and message ordering.

- Handle edge-to-cloud and hybrid IoT data flows.

Cloud & Platform Engineering :

- Design and optimize IoT data solutions on AWS, Azure, or GCP (IoT Core, IoT Hub, IoT Central, etc.).

- Select and implement appropriate data storage technologies: Time-series databases (InfluxDB, TimescaleDB, AWS Timestream) Data lakes (S3, ADLS, GCS) Data warehouses (Redshift, Snowflake, BigQuery, Synapse) Drive cloud cost optimization, performance tuning, and scalability.

Data Processing & Analytics :

- Architect data processing frameworks using Spark, Flink, Databricks, or similar platforms.

- Enable real-time analytics, alerts, and dashboards for operational and business insights.

- Support downstream AI/ML, predictive maintenance, anomaly detection, and digital twin use cases.

Data Governance, Security & Compliance :

- Define data governance frameworks including data quality, lineage, metadata management, and lifecycle policies.

- Ensure data security, encryption, access control, and compliance with industry standards (ISO, GDPR, SOC, etc.).

- Implement monitoring, observability, and audit mechanisms across the IoT data ecosystem.

Leadership & Stakeholder :

- Collaboration Act as a technical authority and mentor for data engineers and IoT platform teams.

- Collaborate with product managers, solution architects, and business stakeholders to translate requirements into scalable solutions.

- Review designs, conduct architecture reviews, and drive technical decision-making.

Required Skills & Experience :

Core Experience :

- 12+ years of overall experience in data architecture, data engineering, or IoT platforms.

- 5+ years of hands-on experience designing and implementing IoT data solutions at scale.

- Proven experience with real-time streaming and event-driven architectures.

Technical Skills :

- Strong expertise in IoT protocols (MQTT, CoAP, AMQP, HTTP). Deep knowledge of cloud platforms: AWS / Azure / GCP (IoT services, data services).

- Hands-on experience with streaming platforms (Kafka, Kinesis, Event Hubs).

- Proficiency in big data processing (Spark, Databricks, Flink).

- Experience with SQL & NoSQL databases, time-series databases, and data lakes.

- Good understanding of APIs, microservices, and containerized architectures (Docker, Kubernetes).

Programming & Tools :

- Proficiency in Python, Java, or Scala. Experience with CI/CD pipelines, infrastructure as code (Terraform, ARM, CloudFormation).

- Familiarity with monitoring and observability tools. Good to Have Experience with Edge Computing and device management.

- Exposure to Digital Twin platforms.

- Background in manufacturing, automotive, energy, utilities, or smart infrastructure domains.

- Cloud certifications (AWS Solutions Architect, Azure Architect, GCP Professional Architect).

Soft Skills :

- Strong analytical and problem-solving abilities.

- Excellent communication and stakeholder management skills.

- Ability to work in cross-functional, global teams.

- Strategic mindset with hands-on execution capability.