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Cloud Data Platforms

Build your data foundation.

Modern cloud data infrastructure that scales with your business. Warehouses, lakes, and platforms designed for analytics excellence.

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99.9%
Uptime SLA
10x
Query Performance
2-4wk
Time to Deploy
Modern Data Stack

Built layer by layer.

Serving Layer
APIs, dashboards & real-time queries
Looker PowerBI Metabase
L4
Orchestration
Scheduling, monitoring & alerting
Airflow dbt Dagster
L3
Compute Engine
Transformation, modeling & ML
BigQuery Spark dbt
L2
Storage Layer
Data lake, warehouse & object storage
BigQuery GCS PostgreSQL
L1
Ingestion
ETL/ELT connectors & streaming
Airbyte Fivetran Pub/Sub
L0
infra-status.sh
healthy
$ omnicliq infra --check
[ingest] 12 connectors active ✓ syncing
[store] 4.2TB warehouse ✓ healthy
[serve] Endpoints responsive ✓ 99.9% up
✓ Pipeline complete
0
Stack Layers
0
Uptime
0
Connectors
What We Do

Cloud infrastructure that actually scales.

Your data infrastructure is the foundation of every analytics initiative. Get it right, and everything else becomes easier.

We design and build modern cloud data platforms using Snowflake, BigQuery, Redshift, and other enterprise-grade technologies. Our architectures are designed for elasticity, performance, and cost-efficiency--scaling seamlessly from gigabytes to petabytes.

Whether you're migrating from legacy systems, building greenfield infrastructure, or optimizing existing platforms, we bring deep technical expertise and battle-tested patterns to ensure your data foundation supports your business growth.

The Omnicliq advantage.

01

Cloud-Native Expertise

Deep experience with Snowflake, BigQuery, Redshift, and Azure Synapse. We know which platform fits your needs.

02

Scalable Architecture

Designed to grow with your business. Start small, scale infinitely without re-platforming.

03

Cost Optimization

Right-size your infrastructure with pay-per-use models. Save 40-60% vs. traditional databases.

04

Security First

Enterprise-grade security with encryption, access controls, and compliance frameworks built-in.

05

Performance Tuning

Optimized query performance with proper clustering, partitioning, and materialization strategies.

06

Future-Proof Design

Flexible architecture that adapts to new data sources, use cases, and technologies.

Our proven process.

01

Assess

Analyze current data landscape, identify pain points, and map requirements to cloud platform capabilities.

02

Design

Architect the target state with detailed blueprints for storage, compute, security, and governance.

03

Build

Implement infrastructure, configure environments, and establish monitoring and alerting systems.

04

Optimize

Fine-tune performance, optimize costs, and establish continuous improvement processes.

Fashion E-commerce
Featured Case Study

Premium Fashion Brand.

6.8x
ROAS
+340%
Revenue Growth
€2M
Monthly Revenue
-28%
CPA Reduction
Read full case study

Common questions.

The choice depends on your existing tech stack, budget, and requirements. We typically recommend Snowflake for flexibility, BigQuery for Google ecosystem integration, or Redshift for AWS-heavy environments.

A data lake stores raw, unstructured data at scale. A data warehouse stores structured, processed data optimized for analytics. Modern architectures often combine both in a 'lakehouse' approach.

Basic infrastructure can be set up in 2-4 weeks. A full data platform with integrations, transformations, and governance typically takes 2-3 months.

We follow a phased migration approach: assess current state, design target architecture, migrate in stages with validation, and run parallel systems until cutover is complete.

We implement enterprise-grade security with encryption at rest and in transit, role-based access control, audit logging, and compliance frameworks (GDPR, SOC 2) built into the infrastructure design.

Ready to modernize?

Let's build the data infrastructure that powers your analytics future.

Schedule Infrastructure Assessment