Assessment and data model
We review your sources, reports and business questions to design the right model and data warehouse.
Deliverables
- Inventory of sources and reports
- Data model and target architecture
- Migration plan if needed
Data and analytics
Data engineering and analytics: one reliable source for decisions
We bring your scattered data into a data warehouse, with automated pipelines and reports your team can query without asking IT.
- First call at no cost
- Kickoff in 2 weeks
- The data and code are yours
Team engineering proven at
- Dow Jones
- LATAM Airlines
- TelevisaUnivision
- Deloitte
- Google Cloud
What we solve
If your reports don't match, the problem is in the data
These are the most common symptoms. If you recognize two or more, a data project will save you hours every week.
Reports that don't match
The same metric comes out different depending on who builds the report.
Data across many tools
ERP, CRM, spreadsheets and marketing with no single version.
Processes that take hours
Slow loads and transformations that delay decisions.
Everything depends on IT
Every new question is a ticket and a wait.
Pending migrations
An old warehouse or orchestrator nobody dares to move.
No data governance
Nobody knows who owns each dataset or whether it is up to date.
What we do
From scattered data to data-driven decisions
Pipelines and data warehouse
We build ingestion and transformations on BigQuery or Snowflake with dbt or Dataform, orchestrated and tested.
Deliverables
- Automated ingestion from your sources
- Versioned, tested transformations
- Orchestration with Airflow or MWAA
Semantic layer and reporting
We define each metric once and publish it in dashboards your team uses on its own.
Deliverables
- Semantic layer (Looker / LookML or other)
- Dashboards for leadership and operations
- Data governance standards
Team experience
Data platforms already running real operations
Data projects our team designed and operated in media, financial information and consulting.
Media · streaming
Data warehouseChallenge
A high-traffic streaming platform needed a central base for its subscription and marketing data.
What was built
Together with Google engineers, architecture and scaling of the BigQuery data warehouse, Dataform ingestion and a Looker semantic layer.
Media · financial information
PipelinesChallenge
A business-critical data process took hours to run.
What was built
Redesign with relational joins and pre-aggregation, as part of a migration from Airflow to MWAA with dbt.
Consulting · corporate finance
Master dataChallenge
A corporate performance system needed reliable finance and HR figures.
What was built
Backend for multidimensional finance and HR cubes, with penny-accurate ledger reconciliation and duplicate-entity detection.
How we work
Short sprints, weekly demos, no black boxes
- 1
First call
no costA conversation with a solutions architect to understand your challenge and tell you honestly whether we are the right fit.
- 2
Assessment and plan
in writingWe review your systems and goals and deliver scope, technology, timeline and price. You approve before we start.
- 3
Sprints with demos
every weekYou see working progress, not slide decks. We adjust priorities with you along the way.
- 4
Delivery and handover
documentedCode, documentation and sessions with your team so it can operate without us.
Security
Your data and your code, under your control
We work inside your accounts and by your rules. When we finish, everything stays with you.
NDA before we start
We sign a confidentiality agreement before seeing any system or data.
The code and credentials are yours
Repositories, cloud accounts and keys in your company's name.
Least-privilege access
We only ask for what each task needs, and you can revoke it at any time.
Documentation included
Architecture, operations and technical decisions in writing with every delivery.
Engagement models and pricing
How to work with us
The first call is at no cost. Then you choose: an assessment to define the plan, a fixed-scope project or a team that moves forward with you month by month.
01 · Assessment
Assessment
On request
Billed hourly
- Sessions with a solutions architect
- Review of your systems, data and goals
- Written plan with scope, technology and price
02 · Per project
Per project
On request
Fixed price
- Fixed scope and price
- Payments per delivered milestone
- Weekly progress demo
- Documentation and handover
03 · Dedicated team
Dedicated team
On request
Fixed monthly fee
- 2-week sprints
- Cloud, data, software and AI in one team
- Scale up or pause with no penalty
- One assigned technical lead
Prices in USD, before VAT. The final price depends on scope.
FAQ
Frequently asked questions about data
Do you work with BigQuery or Snowflake?
Both, and with AWS. We choose based on your cloud, volume and budget; if you already have one, we build on it.
What is a semantic layer and why does it matter?
It is where each metric (sales, churn, margin) is defined once so every report uses the same formula. That way the numbers match no matter who builds the dashboard.
Can you migrate our data warehouse or our Airflow?
Yes. The team has migrated data platforms from GCP to AWS with Snowflake and moved Airflow to MWAA with dbt. We plan the migration so your reporting doesn't stop.
Do we need clean data to start?
No. Cleaning and standardization are part of the work: they live in the transformations, with tests, so they don't depend on manual fixes.
Who owns the data and the code?
You do. Everything lives in your cloud accounts and repositories from day one.
How much does a data project cost?
The first call is at no cost. The assessment is billed hourly and ends with a written plan with a price; then you can choose a fixed-scope project or a dedicated team.
Tell us which data you want to put in order
On the first call, at no cost, we review your sources and reports and propose the next step: an assessment with a written plan, a project or a dedicated team.
- First call at no cost
- Reply within 1 business day
- NDA if you need it