Data Analytics Engineering Services
Clean pipelines, tested transforms, and analytics-ready data — every morning
What is Analytics Engineering Consulting?
Analytics engineering consulting focuses on creating clean, well-modeled, and accessible data pipelines — bridging the gap between raw data and actionable insight.
Analytics engineers sit between data engineers and analysts. They build robust, tested data models that power self-service dashboards, reduce manual data work, and increase trust in reporting.
At Valiotti Data, we deliver data analytics engineering services that help you stay current, scalable, and efficient — all while improving data quality and documentation. From dbt setups to transformation logic and team enablement, we make your data infrastructure work for you.
Benefits of Analytics Engineering
Streamlined Data Transformation
Well-Documented Data
Adaptation to Modern Tools
Data Quality Improvement
Problems & Solutions
Data Transformation Complexity
Our analytics engineers handle data extraction, cleaning, and modeling — automating the transformation process and ensuring accuracy at scale.
Rapid Evolution of Data Tools
We build analytics layer using the latest best practices: dbt for transformations, cloud-based warehouses for scale, and more.
Reliance on Data Teams
We structure your data so non-technical teams can explore and analyze without bottlenecks, using trusted sources and documentation.
Built to remove every barrier
Month-to-Month
No long-term contracts. Stay because the results speak for themselves, not because you're locked in. Cancel with 30 days notice.
NDA from Day One
Your data, strategies, and competitive intelligence stay confidential. Mutual NDA signed before any engagement begins.
First 30 Days Guarantee
If we haven't delivered at least 3 actionable data wins in the first 30 days, the first month is on us. No questions asked.
Your IP, Always
All dashboards, pipelines, documentation, and code belong to you. Full knowledge transfer is built into every engagement.
US & EU Time Zones
Core team operates across EST-PST and CET. Async updates daily. Sync meetings on your schedule, not ours.
Transparent Reporting
Weekly progress updates with measurable outcomes. You'll always know exactly what we're working on and why it matters.
Not sure where to start?
Take our 5-minute CDO Healthcheck. Get a personalized scorecard across data ownership, metrics culture, and trust in data — before committing to anything.
Take the CDO Healthcheck →Your data stays secure
Mutual NDA
Signed before any data access. Your competitive intelligence stays confidential.
SOC 2 Compatible
Our processes align with SOC 2 Type II controls. We work within your existing compliance framework.
GDPR & CCPA Ready
All data handling follows privacy regulations. We never store client data on personal devices.
Your Infrastructure
We work inside your systems — your cloud, your tools, your access controls. Nothing leaves your perimeter.
What our clients say
"The Valiotti Data team has built an analytics infrastructure for Simple App. They analyzed all data streams, designed a data lake, developed microservices for statistics collection, deployed a Kafka cluster to achieve scalable and fail-safe streaming. Next, they deployed Clickhouse on AWS servers, as a solution for increased performance, configured marketing reports and analytics for the database, including ROI analysis. We have built a productive сollaborative partnership, our teams share ideas and offer effective solutions to arising challenges. We are very happy with our cooperation!"
“Valiotti Data has enabled us to react much more quickly and appropriately to signals and to improve day-to-day operational outcomes.”
"We’ve worked directly with Nikolay on multiple long and short-term projects. The results were outstanding! Nikolay and his team delivered fantastic results in a professional manner for a global SaaS company based in Europe with +800 employees. They possess technical skills that are extremely hard to find in the tech market today. Valiotti helped us build our global data platform to empower customer-facing analytics products that excelled. Documentations, code-quality and cross-communications were very professional. I’m looking forward to my next project with Nikolay and his team!"
"Valiotti Data has wonderful people and professionals in their team. Our company required technical assistance in maintaining and developing the existing data warehouse. Data experts from Valiotti quickly grasped the essence of the project and since then the team has been the strongest support for our analytics department. Many tests have been successfully passed and no less awaits us ahead. We sincerely look forward to further collaboration with such an excellent team. Thanks very much!"
Results we've delivered
Frequently asked questions
What do data analytics engineering firms do?
Data analytics engineering firms help businesses structure and transform their data for analysis. This includes building scalable pipelines, implementing tools like dbt, ensuring data quality, documenting transformations, and enabling teams to perform self-service analytics — without relying on constant support from data engineers.
What is analytics engineering?
Analytics engineering is the discipline of transforming raw data into clean, reliable, well-documented datasets ready for analysis. Analytics engineers use tools like dbt to build data models, implement testing, and create documentation. They bridge the gap between data engineers (who build pipelines) and data analysts (who create insights).
Do I need an analytics engineer or a data engineer?
Data engineers build and maintain the infrastructure: pipelines, warehouses, and integrations. Analytics engineers focus on the transformation layer: cleaning data, building dimensional models, and ensuring data quality. If your data is already in a warehouse but analysts struggle with messy, undocumented tables, you need an analytics engineer.
What tools do analytics engineers use?
The modern analytics engineering stack typically includes: dbt (data transformation and documentation), a cloud warehouse (Snowflake, BigQuery, Redshift), Fivetran or Airbyte (data ingestion), Git (version control), and testing frameworks. dbt has become the industry standard, with 30,000+ companies using it as of 2026.
From our blog
Data analysis has gone mainstream, carrying a dense vocabulary along with it. With so much jargon being tossed around by data scientists, we wanted
Is it possible to create a lean governance program in a strict regulatory environment? Can you reduce its complexity without incurring undue risk? Where
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