Datasirpi
Data Engineering Practice

Turn fragmented data into a trusted operating asset

We build governed data foundations for analytics, AI and real-time decision-making. Our engineering-first approach ensures stability at scale.

99.9%
Data Reliability
40%
Infrastructure Savings
10x
Faster Insights
Zero
Data Silos
01

Architect

Data strategy and target architecture. Governance, security and catalog.

02

Build

Data lakes, lakehouses and warehouses. Batch, streaming and ETL/ELT.

03

Organize

Data mesh and domain data products. Quality, lineage and master data.

04

Activate

BI, analytics and real-time insights. AI/ML foundations and DataOps.

A connected data value chain

Sources
Ingest
Lake / Lakehouse / Warehouse
Data products
Analytics & AI

Enterprise Capabilities

Future-proof stacks designed for elite performance.

Modern Data Stack

End-to-end implementation of Snowflake, Databricks, and BigQuery ecosystem. We specialize in dbt-driven modeling and advanced warehouse optimization.

ELT/ETLData ModelingCloud Native

Data Governance

Automated PII detection, fine-grained access control, and comprehensive data lineage.

Real-time Streaming

Ultra-low latency pipelines using Kafka, Flink, and Spark Streaming for instantaneous business intelligence.

Data Quality as Code

Shift-left testing for data. We implement automated validations that block bad data before it hits your production warehouse.

Explore Methodology

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