Atharva Khole
Data Engineer
Databricks · dbt · Airflow · Kafka · SQL Server · Redshift · Postgres · TimescaleDB · Python
I build data infrastructure for industries where bad data has real-world consequences:
- Manufacturing
- Supply chains
- Financial operations
- Industrial systems
Currently at ZIDEA, working across multiple client engagements simultaneously, each with a different stack, team, and problem domain.
What I Work On
I’ve built lakehouse, analytics, and orchestration systems across:
- Automotive manufacturing
- NBFC lending
- Retail / FMCG distribution
- Industrial IoT
The environments are usually less interesting than the constraints:
- 11-year-old SQL Server estates
- Legacy SSIS pipelines
- Unreliable VPN connections
- Hundreds of inconsistent data feeds
- SCADA systems with no historical persistence
- Business-critical workflows held together by tribal knowledge
Typical Engagement
Most projects start with some combination of:
- Data silos
- Inconsistent source systems
- Poor observability
- Fragile pipelines
- Missing ownership
- Operational bottlenecks
And end with:
- Reliable ingestion
- Clear lineage
- Maintainable data models
- Operational visibility
- Data people can actually trust