Analytics engineers who sit between raw data and business decisions — building the transformation layer, semantic layer, and data models that make dashboards trustworthy and self-serve possible.
★★★★★ 5.0 on Clutch/Snowflake & Databricks Partner/dbt Core & dbt Cloud certified
Transformation layers, semantic layers, and data models that give analysts and stakeholders data they can trust.
Build a modular, tested, version-controlled transformation layer using dbt Core or Cloud. Staging, intermediate, and mart layers with full lineage, data quality tests, and documentation your analysts can navigate.
Design dimensional models, one big table strategies, or wide denormalised marts that match how your business asks questions — not just what was easiest to load.
Define a single source of truth for metrics — revenue, activation, churn — using dbt Semantic Layer or LookML so every dashboard and data consumer works from the same numbers.
Build dashboards and self-serve analytics on top of a well-modelled data layer using Looker, Tableau, Power BI, or Metabase. Designed for business stakeholders who don't need to write SQL.
Instrument models with dbt tests, source freshness checks, and anomaly detection so your analytics team stops second-guessing numbers and starts making decisions.
Most analytics teams inherit a warehouse full of raw tables and no transformation layer. We build the layer that turns it into something analysts can use without a data engineer beside them.
We don't bolt dbt on at the end. Transformation logic, tests, documentation, and CI/CD are designed as one system — not separate concerns handed to different people.
We design marts that match how your business asks questions, not how the source data happens to be structured. Analysts find what they need without hunting through 200 tables.
We define metrics once in the semantic layer so Revenue in Tableau matches Revenue in the board deck. No more metric discrepancy meetings.
dbt docs, model READMEs, and a walkthrough your analysts can return to. We don't build black boxes.
Transformation layers and BI environments that analytics teams actually use daily.
Designed and built a full dbt project consolidating product events, Stripe billing, Salesforce CRM, Zendesk support, and ad spend into named marts. Analysts went from writing custom SQL against raw tables to clicking into documented marts with freshness indicators.
Rebuilt a Looker instance where metric definitions had drifted across 60 Explores. Unified revenue, margin, and returns metrics in a single LookML semantic layer. One source of truth across 12 dashboards consumed by the merchandising, marketing, and finance teams.
★★★★★Before this engagement, every analyst had their own version of the revenue formula. Now we have one definition, documented in dbt, tested daily, and trusted by the CFO.
Head of Analytics, SaaS
★★★★★The dbt layer they built is the first thing our new analysts learn. It's documented well enough that they can be productive in a week without needing to ask the data team.
Director of Data, eCommerce
Whether you need a dedicated analytics engineering function, embedded expertise, or a scoped dbt build.
A team of analytics engineers working exclusively on your transformation layer, semantic layer, and BI stack. Best for companies that need to build or rebuild a complete analytics foundation.
Embed analytics engineers into your existing data team. They join your dbt project, standups, and sprint ceremonies from day one. Best for scaling without a full hiring cycle.
Fixed-scope dbt layer, data model redesign, or semantic layer implementation. We own the delivery and hand over documented, tested, production-ready work. Best for defined analytics projects.
Audit source systems, existing SQL logic, key business metrics, and how analysts currently work.
Design staging, intermediate, and mart layers. Agree metric definitions and semantic layer structure before build.
dbt model development, test coverage, documentation, and CI/CD pipeline setup.
Data reconciliation against existing reports, quality test runs, and stakeholder review of marts.
dbt docs walkthrough, model READMEs, and onboarding session. Your analysts own what we built.
Whether you're starting a dbt project from scratch, refactoring an existing one, or rebuilding metrics that mean different things in different dashboards — we'll help you design the right model before any SQL is written.
Hello, we are BRILLIAN’S. Trying to make an effort to put the right people for you to get the best results. Just insight !
