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

- IIo T Dear Folks, We have an exciting opportunity for the above role@TAO Digital Solutions () Interested candidates please forward your updated resume to the following email ID (mohan.kaliappan@) ASAP.

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 Preferred platform / tool exposure: Core engineering : Python, SQL, Py Spark/Scala, Spark, Kafka/Confluent, dbt, Airflow/Dagster, REST/Graph QL APIs, Git, Docker/Kubernetes, Terraform or equivalent Ia C.

Lakehouse / analytics : Databricks Delta Lake, Snowflake, Big Query, Redshift, Synapse/Fabric

- Apache Iceberg/Hudi familiarity is valuable.

Cloud : robust 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/Big Query.

Industrial / edge : AWS Io T Core/Site Wise/Greengrass/Twin Maker, Azure Io T Hub/Io T 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, Service Now; 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, Io T/IIo T, 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.

📌 Principal Data Engineering Architect (Hyderabad)
🏢 Tao Digital Solutions
📍 Hyderabad