Data Engineering
Technology expertise for data engineering and platform initiatives across enterprise environments.
Capabilities / Data Analytics
Make enterprise data more useful to the decisions ahead.
- Data Engineering
- Analytics & Business Intelligence
- Data Platforms
Our approach
CSS supports data and analytics initiatives with expertise across data engineering, modern data platforms, analytics and business intelligence. Scope is aligned to the organization’s systems and intended outcomes.
Areas of focus
Analytics & Business Intelligence
Support analytics and reporting initiatives that help teams access and interpret business data.
Data Platforms
Talent and project delivery for work across established enterprise data platforms.
What we deliver
Data platform engineering
Modern data platforms and pipelines on cloud warehouses and lakehouse technologies.
Data integration and quality
Ingestion, transformation and quality controls that make data trustworthy.
Business intelligence and dashboards
Reports and dashboards designed around the people who use them.
Advanced analytics
Statistical and machine learning analysis that moves from describing results to predicting them.
Data governance
Ownership, cataloging and access practices that keep data usable and compliant.
How we deliver
01
Assess
Map the data landscape, sources and reporting needs.
02
Architect
Define the platform, models and governance approach.
03
Build
Engineer pipelines, models and reports.
04
Enable
Train teams and support adoption so insight gets used.
Technology landscape
Relevant expertise, aligned to your environment.
Snowflake
Databricks
Python
Spark
Power BI
Tableau
How we engage
01
Project delivery (SOW)
A defined scope with agreed deliverables and milestones, and a CSS team accountable for the outcome.
02
Managed services
Ongoing support and continuous improvement of a platform or environment under an agreed service model.
03
Team augmentation and direct hire
Specialists who join your team, from contract and contract-to-hire to permanent placements.
Common questions
Which data platforms do you work with?
Snowflake, Databricks, Spark and the major cloud data services, together with Power BI and Tableau for reporting.
Can you help us modernize an existing warehouse?
Yes. We typically assess the current estate, define a target architecture and migrate in phases so reporting stays available.
How do analytics and AI fit together?
Reliable, governed data is the foundation for AI. Many engagements start with the data platform and build toward machine learning use cases.
Next step
Share the goal, your current environment and the timeline. We will help shape the right team and approach.