Cloud & Data Engineering

Build the foundation that products and intelligence depend on.

We engineer cloud and data environments around the applications and operations they need to support. That includes infrastructure, storage, processing, application data flows and the foundations required for analytics and AI.

Capabilities

Engineering across the layers that make the system work.

01

Cloud architecture

Design application infrastructure around workload, availability, security and operational requirements.

02

Data architecture

Structure application and enterprise data so it can support transactions, reporting and downstream intelligence.

03

Processing pipelines

Move and transform data between applications, storage, analytics and AI workloads.

04

Storage & compute

Select and structure infrastructure appropriate to application, media, data and processing patterns.

05

Analytics foundations

Prepare consistent data flows for reporting, operational visibility and decision support.

06

AI infrastructure

Support model services, asynchronous jobs, queues, storage and compute required by AI-enabled applications.

System architecture

From business requirement to operating system.

We connect experience, application logic, data, integrations and infrastructure so the technology works as a coherent environment rather than a collection of disconnected components.

01Source Systems
02Data Pipelines
03Cloud Platform
04Analytics & AI
05Applications
Where it fits

Engineering around the stage and shape of the business.

The right approach depends on what already exists, what the organization needs to accomplish and how the system is expected to evolve.

01

Digital platforms

Provide reliable infrastructure and data services underneath web, mobile and enterprise products.

02

AI workloads

Coordinate compute, storage, queues and data around model-driven processing.

03

Enterprise reporting

Connect operational sources into more consistent data structures for analysis and visibility.

04

Platform modernization

Move applications and data toward architectures that are easier to operate, extend and integrate.

Cloud & Data Engineering
Engineering perspective

Cloud and data architecture should follow the workload.

The right infrastructure depends on what the system actually does: transaction patterns, processing intensity, media, integration, data volume, availability and the operational requirements around it.

Explore Our Work
Cloud & Data Engineering

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