Cloud & Data Engineering
Enterprise cloud data lakehouses, automated ETL/ELT pipelines, and analytics infrastructure.
Service Overview
Modern businesses need clean, accessible, and real-time data to drive decision-making. We build production cloud data pipelines and lakehouses using Azure Data Factory, Databricks, Snowflake, and Microsoft Fabric.
Who This Service Is For
Practical Challenges We Solve
What We Deliver
Scope Boundaries & Clear Commitments
- •Pipeline development
- •Lakehouse schema design
- •Data quality checks
- •Alerting & monitoring setup
- •Monthly cloud provider usage charges (Azure/AWS/Snowflake)
Target Use Cases & Workflows
How We Work & Delivery Methodology
Medallion Architecture (Bronze -> Silver -> Gold) ensuring data hygiene, high performance, and enterprise governance.
Core Technologies & Toolstack
Cost & Timeline Factors
Project estimates vary depending on technical complexity rather than flat template rates. Key cost drivers include:
- •Number of distinct data sources integrated
- •Volume of daily data ingested (GBs/TBs)
- •Real-time streaming vs daily batch sync requirement
Handover, IP Ownership & Support
Client Preparation Checklist
To help us launch your project quickly, having these items ready is beneficial:
- •Access to source database read-replicas & API keys
- •Data dictionary and field definitions list
- •Target cloud subscription access
Frequently Asked Questions
Related Engineering Practices
Generative AI & Agent Development
Custom RAG pipelines, LLM fine-tuning, and autonomous AI agents grounded in private data.
Data Analytics & Business Intelligence
Executive Power BI dashboards, automated KPI reporting, and self-service analytics.
AI Strategy & Consulting
AI roadmap planning, feasibility auditing, technology evaluation, and ROI modeling.
Discuss Your Project
Share your software, cloud, or data project requirements — our engineering leads will get back to you within 24 hours.