Workstream 01
Architecture and design
Lake vs warehouse vs lakehouse decisions based on scale, budget, skill profile, and roadmap.
CAPABILITIES
Data platform
Your data, unified and queryable. We architect governed platforms that serve analytics, ML, and product teams from a trusted, shared source of truth.
Architecture and design
Ingestion and integration
Modeling and transformation
Capability focus areas
Warehouse / lakehouseTransformationCatalogGovernance
What we do
Workstream 02
Ingestion and integration
Consistent ingestion from APIs, event streams, SaaS systems, and CDC across 50-500+ sources.
Workstream 03
Modeling and transformation
Dimensional and medallion modeling with dbt-driven transformations, tests, and documentation.
Workstream 04
Governance and cataloging
Lineage, access control, and PII classification with catalog workflows teams actually use.
Workstream 05
Semantic layer
Define metrics once and reuse consistently through semantic modeling tools.
Workstream 06
Self-serve enablement
Train analysts and product teams with tooling standards and practical office-hour support.
Workstream 07
Operating model design
Define ownership, SLAs, and change-management workflows so platform reliability scales with organizational complexity.
How we work
01
Discovery and constraints
Assess source systems, stakeholders, governance requirements, and target data products.
02
Platform blueprint
Design architecture, ownership model, and rollout phases with clear quality and governance gates.
03
Implementation
Ship ingestion, transformation, and access layers incrementally with observability and documentation.
04
Adoption and handoff
Enable internal teams to operate and expand the platform independently.
Tech we use
Warehouse / lakehouse
ClickHouseSnowflakeBigQueryDatabricksIceberg + Trino
Transformation
dbtSQLMesh
Catalog
DataHubAtlanAmundsenUnity Catalog
Governance
Great ExpectationsSodaMonte Carlo
Semantic
CubeMetricFlow
Featured case study
Proof in production
We built a HIPAA-compliant lakehouse unifying 28 sources and reduced compliance review cycles from weeks to hours.
Read case studyQuestions we get
Snowflake or ClickHouse?
Both are strong. We choose based on workload shape, governance needs, and total-cost trajectory.
Do we need a data catalog?
Once usage scales beyond a small core team, a catalog and lineage model become critical for trust and velocity.
Can we phase platform modernization?
Yes. We typically modernize in slices to avoid long freeze periods and reduce migration risk.
Need a platform your whole org can trust?
We can design and deliver a governed data foundation aligned to analytics and ML goals.
Architect your platform