Principal Data Engineer
Building data platforms that teams can trust.
10+ years turning raw data into reliable platforms, from statistical models to lakehouse architectures on Microsoft Fabric and Databricks.
- Years in data
- 20+
- Pipelines in production
- 60+
- Scale lakehouses
- PB
- Career arcs: DS → DE
- 2
About
From data scientist to data engineer
I'm Nanda Kishore T, founder of DatumQuantum and data professional with over 20 years of IT experience, including more than 10 years across data science, analytics, and data engineering. I began my data career in data science and analyst roles, building analytical models and generating business insights. Over time, I moved into data engineering, where I now focus on designing reliable data platforms, Lakehouse architectures, and production-ready analytics solutions using Azure, Databricks, and Microsoft Fabric.
2021 — Present
Principal Data Engineer
Lakehouse platforms on Azure, Databricks and Microsoft Fabric. Governance, streaming, cost optimization and platform enablement for analytics and ML teams.
2015 — 2020
Senior Data Scientist
Predictive models for churn, demand forecasting and risk. Moved models from notebooks to production, which sparked the shift toward engineering.
2007 — 2014
Scripting Analyst / Lead Engineer
Working on Scripting Languages and leading a teams.
Technical skills
The tools I use to build and run data platforms.
Microsoft Fabric & Azure
- OneLake
- Fabric Lakehouse
- Fabric Data Warehouse
- Data Factory Pipelines
- Real-Time Intelligence
- Power BI Direct Lake
- Azure Data Lake Gen2
- Azure Synapse
- Azure DevOps
Databricks
- Unity Catalog
- Delta Lake
- Lakeflow / DLT
- Structured Streaming
- Databricks SQL
- MLflow
- Workflows
- Asset Bundles
- Photon
Engineering
- PySpark
- SQL
- Python
- Scala
- dbt
- Kafka
- Terraform
- CI/CD
- Data Quality
Data Science
- Statistical Modeling
- Forecasting
- Feature Engineering
- scikit-learn
- Experimentation
- MLOps