Data Engineering & Warehouse Modernization
Part of Cloud & App ModernizationDecisions are only as good as the data behind them - and legacy warehouses and brittle ETL jobs make good data hard to get. ALINEDS modernizes data platforms for government and regulated organizations, migrating and consolidating data into modern cloud warehouses with reliable pipelines. Using Snowflake, Azure Data Factory, and modern ETL/ELT, we replace slow, siloed reporting with a governed, performant data foundation - so your teams get trustworthy data, faster, without the maintenance drag of aging on-prem systems.
Why it matters
Legacy data warehouses are expensive, slow, and increasingly unsupportable - and the manual ETL around them breaks quietly. For public agencies, that means late reports, inconsistent numbers, and analysts stuck wrangling instead of analyzing. Modernizing the data platform is what makes reporting reliable and unlocks analytics and AI on top - which is why it's the foundation for everything data-driven you want to do next.
What you get
Data platform assessment & roadmap
We evaluate your current warehouse and pipelines and plan the migration to a modern cloud platform.
Cloud data warehouse migration
We migrate and consolidate data into modern warehouses (e.g., Snowflake) for performance and scale.
Modern ETL/ELT pipelines
We rebuild data pipelines on Azure Data Factory and ELT patterns for reliability and speed.
Data consolidation
We bring siloed sources together into one governed, queryable platform.
Governance & lineage
We build in access control, quality checks, and lineage so the data is trustworthy and auditable.
Analytics enablement
We deliver modeled, reliable, well-documented data your BI tools and analysts can depend on - so teams spend time on insight, not on wrangling and reconciling numbers.
How it works
Assess
Review the current warehouse, pipelines, and sources.
Design
Plan the target cloud data platform and migration.
Migrate & build
Move data and rebuild pipelines on modern ETL/ELT.
Govern & optimize
Add governance, quality, and performance tuning.
Where it fits
Legacy warehouse to Snowflake
Migrate an aging on-prem warehouse to a modern cloud platform.
Consolidating siloed data
Unify fragmented sources into one governed warehouse.
Fragile ETL modernization
Replace brittle, manual ETL with reliable ELT pipelines.
Reporting performance
Fix slow, unreliable reporting with a performant modern platform.
Key distinctions
Modern cloud warehouse vs. legacy on-prem warehouse
| Aspect | Modern cloud warehouse | Legacy on-prem warehouse |
|---|---|---|
| Scale | Elastic, on demand | Fixed capacity |
| Performance | Fast at scale | Degrades under load |
| Cost | Usage-based | High fixed + maintenance |
| Pipelines | Modern ELT | Brittle manual ETL |
| Governance | Built-in lineage | Often ad hoc |
Compliance & security
Governed and audit-ready
Modernized data platforms are built with governance, lineage, and role-based access, aligned to NIST 800-53 and 800-171 and GovRAMP, with HIPAA or FERPA controls where the data is sensitive. The platform is both performant and audit-ready.
- NIST 800-53
- NIST 800-171
- GovRAMP
- HIPAA
- FERPA
Key terms
- Data warehouse
- A central store optimized for reporting and analytics across consolidated data sources.
- ETL / ELT
- Moving and transforming data into a warehouse - Extract-Transform-Load, or the cloud-favored Extract-Load-Transform.
- Data lineage
- A traceable record of where data came from and how it was transformed.
Frequently asked
How is this different from your AI & Data "Data & Analytics Engineering" service?
This service (Cloud) modernizes and migrates your data platform - warehouses and pipelines. The AI & Data service shapes and serves that data specifically for AI/ML and RAG. Many projects use both: modernize the platform here, then make it AI-ready there.
What cloud data platforms do you use?
Snowflake for the warehouse, Azure Data Factory and modern ETL/ELT for pipelines - matched to your environment.
Why modernize our data warehouse?
Legacy warehouses are costly, slow, and hard to support; modern cloud platforms scale on demand, perform better, and cost by usage.
What's the difference between ETL and ELT?
ETL transforms data before loading it; ELT loads first and transforms in the powerful cloud warehouse - the modern default for scale and flexibility.
Can you consolidate data from many systems?
Yes. Consolidating siloed sources into one governed platform is a core part of the work.
Will our reporting improve?
Typically yes - a performant modern platform with clean pipelines fixes the slow, inconsistent reporting legacy systems produce.
How do you keep sensitive data protected?
With role-based access, governance, and lineage aligned to NIST 800-53/171 and, where relevant, HIPAA or FERPA.
Can you keep our data platform running during the migration?
Yes. We migrate in stages and run old and new in parallel where needed, so reporting keeps working until the modern platform is proven and cut over cleanly.