Data Engineering
Build the data foundation your analytics and AI depend on.
We design and build modern data platforms — ingesting data from your systems, cleaning and modelling it, and making it available for reporting, data science and AI.
- SourcesApps, databases, files, APIs
- PipelinesIngest, clean, validate
- Lakehouse / warehouseModelled and governed
- AnalyticsReports and dashboards
- AIModels and agents
CH 01The challenge
Business problems we solve
Where organizations typically get stuck before engaging NaviCS for Data Engineering.
Data trapped in silos
Customer, finance and operations data sit in separate systems that do not talk to each other.
Fragile pipelines
Scripts and manual exports break without warning, and reports quietly go stale.
Poor data quality
Duplicates, gaps and inconsistent formats undermine trust in every report and model.
Not ready for AI
AI initiatives stall because the data they need is not accessible, documented or governed.
CH 02What we do
Data Engineeringcapabilities
Scope we deliver end to end, or alongside your own team.
Data platform architecture
Lakehouse and warehouse designs sized for your data, users and budget.
Ingestion and pipelines
Batch and incremental pipelines from applications, databases, files and APIs.
Data modelling
Layered, documented models ready for analytics, data science and AI.
Data quality
Automated checks, alerts and reconciliation so issues are caught early.
Governance and security
Access control, lineage and cataloguing to meet internal and regulatory requirements.
Platform migration
Move from legacy databases and on-premise warehouses to modern cloud platforms.
CH 03Use cases
Where it makes a difference
Concrete business applications we design and deliver.
- Use case 01
Unified customer data
Combine CRM, support and transaction data into a single customer view.
- Use case 02
Finance data platform
Automate the data behind management reporting and planning.
- Use case 03
Legacy warehouse modernization
Replace brittle on-premise ETL with maintainable cloud pipelines.
- Use case 04
AI-ready data products
Curated, documented datasets that AI agents and models can use safely.
CH 04How we deliver
From Business Challenge to Business Outcome
How NaviCS takes Data Engineering from business challenge to business outcome.
Discover
Understand the business problem, the people involved, the data and systems in place, and what success looks like.
Design
Define the solution, architecture, data flows and guardrails — and agree on how results will be measured.
Build
Deliver in short, reviewable increments so stakeholders see working software early and often.
Integrate
Connect to your CRM, data platforms, APIs and business applications so the solution fits existing workflows.
Deploy
Release to production with monitoring, access controls, documentation and team enablement.
Improve
Review usage and outcomes, tune models and workflows, and extend what works to new teams.
CH 05Technology
Technologies we work with
We design around the platforms you already use wherever possible.
- SQL / PostgreSQL
- Python
- Docker containers
CH 06AI agent integration
Connected to how your business runs
Well-engineered data is what makes AI agents trustworthy. We expose curated data to NaviCS agents through governed access, so answers and actions are based on the right records.
See how NaviCS agents act across systems- Lakehouse / warehouse
- Semantic models
- Enterprise data APIs
- CRM
- AI agents
CH 07Outcomes
What you can expect
The business results each engagement is designed around. Specific targets are agreed with you during discovery.
- Data from separate systems available in one governed platform
- Pipelines that are monitored, documented and recoverable
- Data quality issues caught before they reach reports
- A foundation ready for analytics, data science and AI
CH 08FAQ
Data Engineering questions, answered
Should we choose a lakehouse or a data warehouse?
It depends on your data types, workloads and existing skills. We compare options against your requirements during design rather than defaulting to one pattern.
Can you work with our existing cloud provider?
Yes. We design around the platform and agreements you already have.
How do you migrate without disrupting reporting?
We migrate in phases, run old and new pipelines in parallel and reconcile outputs before switching reports over.
Do you provide ongoing support?
We can operate and monitor the platform after launch or hand it over to your team with runbooks and training.
CH 09Related services
Often combined with
Data Analytics
Dashboards and reporting that give every team trusted numbers they can act on.Learn moreData Science
Predictive models that forecast demand, flag risk and recommend the next best action.Learn moreCloud Engineering
Modernize applications and infrastructure on scalable, secure cloud platforms.Learn more
Have a business challenge? Let's turn it into an opportunity.
Tell us what you want to improve with Data Engineering. We'll show you how NaviCS would approach it and what a first phase could look like.