Data Architecture
& Insights.
We design and build the data foundations that enterprises run on — from ingestion pipelines to dimensional models to governed warehouses. Clean data, trusted metrics, decisions that hold up under scrutiny.
Diagnosing and Eliminating 64% of BigQuery Operational Costs
When BigQuery spend climbed to $99,000 a month, we identified the root cause: poorly structured models generating redundant query patterns and unoptimized table scans. Through systematic model consolidation and applying clustering and partitioning strategies, we drove monthly spend from $99,000 → $54,000 → $36,000 across successive optimization cycles — without disrupting the teams depending on those pipelines.
64%
Cost Reduction
15+ Yrs
Architectural Tenure
Strategic Impact
Identified runaway query costs traced to poorly structured dbt models generating redundant full-table scans.
Consolidated overlapping models and applied BigQuery clustering and partitioning strategies to eliminate unnecessary data processing.
Drove monthly spend from $99,000 → $54,000 → $36,000 across successive optimization cycles without disrupting downstream teams.
The Modern Data Stack
Ingestion → Transformation → Warehouse.
In that order. Done properly.
Most data problems aren't warehouse problems — they're pipeline and modeling problems. We work across the full stack: ingestion with Fivetran or Airbyte, orchestration with Dagster or Airflow, transformation in dbt, and warehousing in BigQuery, Snowflake, or Redshift — wherever your data lives.
Layer 01 — Ingestion
Fivetran & Airbyte
Automated connectors from your source systems — CRMs, ERPs, databases, SaaS tools — into your warehouse. We've worked with both Fivetran (managed, low-maintenance) and Airbyte (open-source, flexible) and will recommend the right fit for your budget and connector needs.
Layer 02 — Orchestration
Dagster & Airflow
Scheduling, dependency management, and pipeline observability. Dagster's asset-based model pairs naturally with dbt; Airflow handles complex multi-system workflows where you need fine-grained DAG control. We've built production pipelines in both.
Layer 03 — Transformation
dbt
SQL-based transformations with version control, testing, and lineage built in. We use dbt to build the transformation layer that turns raw source data into governed, documented, and auditable models your analysts can trust.
Layer 04 — Warehouse
Warehouse-Agnostic
BigQuery, Snowflake, or Redshift — we work across all three and don't have a preferred vendor. Selection depends on your existing cloud footprint, team familiarity, cost model, and query patterns. We'll give you a direct recommendation based on your situation.
Dimensional Modeling
Star Schema.
Snowflake Schema.
Knowing which to use.
Dimensional modeling is the discipline that separates data warehouses from data dumping grounds. We design fact and dimension tables that reflect how your business actually measures itself — not just how your source systems happen to store data.
Star schemas offer query simplicity and BI layer performance. Snowflake schemas reduce redundancy at the cost of join complexity. The right choice depends on your query patterns, team maturity, and downstream tooling — and we'll give you a direct opinion, not a slide deck of tradeoffs.
Star Schema
Denormalized dimensions surrounding a central fact table. Faster queries, simpler BI tooling, easier for analysts to self-serve. Our default recommendation for most enterprise reporting workloads.
Snowflake Schema
Normalized dimensions that reduce storage redundancy. Better suited for high-cardinality dimensions and environments where data integrity across complex hierarchies is the priority.
Core Capabilities
Platform Modernization
Migrating from legacy on-prem silos to modern cloud data platforms. We handle the architecture, the migration plan, and the governance structure — so you don't inherit yesterday's problems in a new warehouse.
Governance & Compliance
Audit-ready lineage built into every dbt model. For regulated industries — life sciences, healthcare, finance — we design pipelines where compliance is structural, not a checklist applied after the fact.
Standardizing the "Truth"
When every team runs their own numbers and no two match, the problem is upstream. We build the unified dimensional models and metric definitions that give the whole organization one shared "Golden Record" to operate from.
Executive Insights
A well-modeled warehouse makes the BI layer straightforward. From Power BI to Looker to custom D3.js visualizations, we build the reporting layer on top of a foundation that actually supports it.
Ready to Modernize Your Foundation?
We start with an honest audit of your current stack — pipelines, models, warehouse costs, and governance gaps. You'll leave with a clear picture of what's working, what isn't, and what to do about it.
Schedule a Data Platform Audit