Principal Data Engineering Architect

Tao Digital Solutions Inc.; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

TAO Digital Solutions invites an exceptional Principal Data Engineering Architect to shape our Industrial Data Platforms and IIoT strategy. You will own the architecture across AI/ML workloads, edge-to-cloud integrations, and high-volume telemetry for asset-intensive industries.

The ideal candidate has 12–18+ years in data engineering and at least 6+ years in AI/ML, with proven senior leadership and delivery of production-ready platforms used by data science and operations teams.

Qualifications

• 12+ years in data engineering, data platforms, software/platform engineering or architecture.
• 6+ years in AI/ML; 3+ years leading production AI architecture in asset-intensive environments.
• Experience with high-volume telemetry, IoT/IIoT, event/log/time-series data.
• Proven architecture and delivery across at least one asset-intensive industry.
• Platforms used in production by data science/AI and operations teams with SLA, observability and governance.
• Strong security and networking knowledge for hybrid edge-to-cloud and OT/IT integrations.
• Ability to communicate with plant/site engineers, reliability teams, data scientists, cybersecurity, enterprise architects and executives.

Responsibilities

• Architect and own industrial data platforms and IIoT data pipelines.
• Drive governance, observability, and cost controls across analytics platforms.
• Collaborate with data scientists, reliability teams and executives on roadmaps.

Skills

AI/ML leadership

Data architecture

Stakeholder communication

Cloud design patterns

Education

Bachelor's/Master in Computer Science or Engineering

Tools

Python

SQL

PySpark/Scala

Spark

Kafka/Confluent

dbt

Airflow

Dagster

REST/GraphQL APIs

Git

Docker/Kubernetes

Terraform

Databricks

Delta Lake

Snowflake

BigQuery

Redshift

AWS/GCP/Azure

Job description

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

Dear Folks,

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.

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 data—not 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.