Data Architect - IoT Azure

Fractal Analytics · Bengaluru

  • Experience9–13 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted2 Sept 2026
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About Fractal Analytics

Fractal Analytics is hiring in Bengaluru in technology software. This role looks for around 9+ years of experience.

Skills

  • IIoT architecture
  • edge computing
  • cloud ingestion
  • real-time analytics
  • time-series analytics
  • GCP Analytics Stack
  • Pub/Sub
  • Dataflow
  • BigQuery
  • Bigtable
  • Vertex AI
  • InfluxDB
  • TimescaleDB
  • Kafka
  • event-driven architectures
  • Grafana
  • PLC
  • SCADA
  • MES
  • OPC-UA
  • MQTT
  • Modbus
  • data pipelines
  • lakehouse architectures
  • ML/AI
  • IoT security
  • industrial network architectures

The role

A data architect at an industrial manufacturing technology company designs edge-cloud IIoT platforms for real-time analytics, integrating PLC, SCADA, and MES systems with data lakehouses. The role applies GCP Analytics Stack, time-series analytics, and industrial automation to enable predictive maintenance and asset performance monitoring.

Full job description

Responsibilities:

Lead the design and delivery of end-to-end industrial IoT architecture spanning edge to cloud, enabling real-time data ingestion, time-series analytics, and cloud-scale AI/analytics for manufacturing and industrial operations.

Drive platform strategy, standardisation, and scalability of IIoT solutions aligned with enterprise data and AI platforms.

Define and implement edge-cloud IIoT architecture (edge devices, streaming, cloud analytics, AI).

Design real-time data pipelines for high-frequency industrial/time-series data.

Architect integration of OT systems (PLC, SCADA, MES) with cloud data lakehouse platforms.

Lead cloud analytics strategy (streaming, batch, AI/ML on industrial data).

Establish IIoT platform standards (data models, ingestion patterns, governance, security).

Design observability solutions using Grafana + time-series platforms.

Ensure scalability, resilience, and security of IoT ecosystems.

Partner with data, AI, and business teams to enable use cases: Predictive maintenance, asset performance monitoring, quality analytics, energy optimisation.

Success Metrics:

Scalable, standardised edge-to-cloud IIoT platform.

Reliable real-time ingestion and processing of industrial data.

Enterprise adoption of cloud analytics on IIoT data.

Measurable impact on uptime, efficiency, and operational visibility.

Requirements:

Bachelor's/Master's in engineering, computer science, or a related field.

8-12+ years in IoT/IIoT, data platforms, or industrial automation.

Proven experience designing real-time, cloud-scale IIoT architectures.

Required Skills: Architecture and Platforms.

Edge-Cloud Architecture: gateways, edge computing, cloud ingestion, and analytics layers.

GCP Analytics Stack: Pub/Sub, Dataflow, BigQuery, Bigtable, Vertex AI.

Time-Series Platforms: InfluxDB, TimescaleDB, Bigtable.

Streaming and Real-Time Analytics: Kafka / Pub/Sub, event-driven architectures.

Visualisation: Grafana.

Industrial and Integration:

OT systems: PLC, SCADA, MES.

Protocols: OPC-UA, MQTT, Modbus.

Experience integrating factory systems with enterprise data platforms.

Data and AI:

Real-time analytics, data pipelines, and lakehouse architectures.

ML/AI use cases on industrial data (predictive maintenance, anomaly detection).

Security and Networking:

IoT security (device identity, encryption, zero-trust principles).

Industrial network architectures.