Opening For Principal Data Architect - Industrial Data Platforms IIoT

TAO Digital; Hyderabad; On-site; INR 9,000,000 - 13,000,000; Full time

Job summary

TAO Digital is seeking a Principal Data Engineering Architect to lead industrial data platforms and IIoT initiatives. You will drive architecture across cloud, on-prem, and edge environments, collaborating with data scientists, reliability, cybersecurity, and engineering teams.

The role requires deep expertise in data engineering, IoT data, and scalable platforms, with strong leadership and communication skills to align across plant/site stakeholders.

Qualifications

• 12+ years in data engineering, data platforms or architecture.
• 3+ years owning senior architecture/technical leadership responsibilities.
• Experience with high-volume telemetry, IoT/IIoT data and time-series data.
• Proven delivery across asset-intensive industries with enterprise-scale platforms.
• Knowledge of security and networking for hybrid edge-to-cloud OT/IT integrations.
• Ability to communicate with engineers, data scientists, cybersecurity, and executives.

Responsibilities

• Lead architecture for industrial data platforms and IIoT solutions.
• Collaborate with data science, reliability, and operations teams.
• Ensure observability, governance, SLAs, and cost controls for production platforms.
• Design secure hybrid edge-to-cloud integrations and data workflows.

Skills

Python

SQL

PySpark/Scala

Spark

Kafka/Confluent

dbt

Airflow/Dagster

REST/GraphQL

Git

Docker/Kubernetes

Terraform/IaC

Databricks

Delta Lake

Cloud (AWS/Azure/GCP)

IoT/IIoT

OPC-UA/MQTT

Security & Networking

Data governance

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Electrical/Computer/Industrial Engineering or related discipline

Tools

Databricks Unity Catalog

Microsoft Purview

AWS Glue/Lake Formation

Collibra/Alation

Great Expectations / Soda / Monte Carlo

Job description

Exciting Opening for Principal Data Engineering Architect Industrial Data Platforms & IIoT

We have an exciting opportunity for the above role @ TAO Digital Solutions (www.taodigitalsolutions.com)

Experience

12 to 18+ years overall. Candidate should have min 6+ years in AI/ML; 3+ years leading production AI architecture in asset-intensive environments

Pref Industry

Telecommunications; Energy / Oil & Gas; Automotive / Manufacturing; Aerospace / Aviation

Core engineering

Python, SQL, PySpark/Scala, Spark, Kafka/Confluent, dbt, Airflow/Dagster, REST/GraphQL APIs, Git, Docker/Kubernetes, Terraform or equivalent IaC.

Lakehouse / analytics

Databricks + Delta Lake, Snowflake, BigQuery, Redshift, Synapse/Fabric; Apache Iceberg/Hudi familiarity is valuable.

Cloud

strong depth in at least one of AWS, Azure or GCP and architectural familiarity with a second. Examples: S3/Glue/EMR/Kinesis/MSK; ADLS/Data Factory/Event Hubs/Fabric; GCS/Dataflow/Pub/Sub/BigQuery.

Industrial / edge

AWS IoT Core/SiteWise/Greengrass/TwinMaker, Azure IoT Hub/IoT Edge/Digital Twins, MQTT brokers, OPC-UA gateways; familiarity with AVEVA PI/OSIsoft historians, SCADA/DCS and MES/MOM.

Governance

Databricks Unity Catalog, Microsoft Purview, AWS Glue/Lake Formation, Collibra/Alation, data-quality/observability tooling such as Great Expectations, Soda, Monte Carlo or equivalent.

Operational applications

IBM Maximo, SAP PM/EAM, ServiceNow; telecom OSS/BSS/NMS; automotive PLM/MES; aerospace MRO/engineering systems are desirable depending on domain.

Experience & qualifications

12+ years in data engineering, data platforms, software/platform engineering or architecture, with 3+ years owning senior architecture/technical leadership responsibilities.

Proven experience with high-volume, high-velocity telemetry, IoT/IIoT, event, log or time-series datanot only traditional BI/warehouse workloads.

Demonstrated architecture and delivery across at least one asset-intensive industry, with working understanding of maintenance/reliability or operational workflows.

Evidence of building platforms that are used in production by data science/AI and operations teams, including clear SLAs, observability, governance and cost controls.

Strong knowledge of security and networking considerations for hybrid edge-to-cloud and OT/IT integrations.

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Electrical/Computer/Industrial Engineering or related discipline; equivalent industry experience acceptable.

Ability to communicate with plant/site/network engineers, reliability teams, data scientists, cybersecurity, enterprise architects and executive stakeholders.