We engineer cloud-native pipelines, resilient platforms, and automated analytics that accelerate time-to-insight, optimize cost, and keep data reliable across Snowflake, Databricks, Azure, and AWS.
Modern data platform setup with automated ingestion, ETL/ELT, and cloud architectures across Snowflake, Databricks, Azure, and AWS—governed, secure, and observable.
Business dashboards and metrics layers that standardize KPIs, enable self-serve analytics, and keep leadership aligned on a single version of truth.
Predictive models and GenAI prototypes built with full MLOps—experimentation, deployment, and monitoring to keep models healthy in production.
We lead with business-first discovery, ship reference architectures with automated testing and observability, and deliver in increments—first win in 6–8 weeks—while aligning to your cloud governance model and high documentation standards.
| Layer | Options |
|---|---|
| Ingest | Event streams, APIs, CDC, files |
| Transform | Templated ETL/ELT patterns + tests |
| Serve | Warehouse, lakehouse, feature store |
| Observe | Data contracts, lineage, quality gates |
| Operate | CI/CD, runbooks, cost optimization |