Enterprise Data Architecture
for Austin's Growth Economy.

Technology & SaaS Scale-Ups

Oracle, Dell, Apple, Google, Meta — plus a dense ecosystem of SaaS companies (Atlassian, Cloudflare, Bazaarvoice) — all face the same challenge: data architectures built for startup scale that break at enterprise scale. We rebuild the data layer — certified data sources on Snowflake, dbt, and BigQuery — with governance that holds as headcount and data volume grow.

Semiconductor & Manufacturing

Samsung Austin Semiconductor, NXP Semiconductors, Silicon Labs, and Applied Materials run complex manufacturing analytics environments. We connect MES, SCADA, and ERP systems — handling high-frequency sensor data for yield analysis, equipment OEE, defect tracking, and supply chain performance — in unified data platforms that serve both operations and leadership.

State Government & Education

As the state capital, Austin houses major Texas government agencies and UT Austin. We understand Texas DIR procurement frameworks, state data residency requirements, and the reporting requirements that span legislative, executive, and public transparency stakeholders. We also work with public higher education institutions managing research and operational data at university scale.

Healthcare & Life Sciences

Ascension Seton, St. David's Healthcare, UT Health Austin, and a growing life sciences cluster generate HIPAA-regulated data at enterprise scale. We build compliant data architectures with Epic/Cerner integrations, clinical data warehouse design, and row-level security for clinical, administrative, and research use cases.

Modern Data Stack Architecture

Snowflake, dbt, BigQuery, or Databricks — designed for your scale, your team, and your AI roadmap. We select the right tools and design the full architecture: ingestion, transformation, governance, and serving layers.

Cloud Data Engineering

End-to-end engineering on Azure, GCP, or AWS. ADF/Dataflow pipelines, Delta Lake, Databricks jobs, and data quality monitoring. We build what we design.

Data Governance & Semantic Layer

Certified dbt models, Microsoft Purview or dbt docs catalog, metric definitions in a semantic layer, and access controls aligned to your Snowflake or BigQuery roles. One version of the truth.

Manufacturing & OT Data Integration

Connecting MES, SCADA, PI historians, and IoT sensor feeds into your analytics platform. Designed for Austin's semiconductor and industrial manufacturing clients.

AI-Ready Data Foundation

Feature engineering pipelines, MLflow experiment tracking, model serving infrastructure — built on the same governed data platform your BI and analytics teams run on.

Data Architecture Audit

A 2–3 week diagnostic: we map your current data sources, identify the architectural debt holding back your analytics, and deliver a prioritised roadmap before any build work begins.

Day Rate

From $1,500/day

Architecture, design, and hands-on data engineering

Project

From $12,000

Scoped data platform builds and architecture designs

Managed Data

From $5,500/mo

Ongoing data engineering and platform management

We are a fast-scaling Austin tech company. Our data architecture was designed for 50 people and we now have 500. How do you fix this?

This is the most common data architecture engagement we run for Austin tech companies. Fast growth creates predictable data problems: data sources proliferate without governance, the same metric shows different numbers in different dashboards, and query performance degrades. We start with a Data Architecture Audit, then rebuild the data source layer on Snowflake, dbt, or BigQuery with certified metric definitions, proper governance, and access controls that scale with your organisation.

Do you have experience with semiconductor and manufacturing data environments?

Yes. Samsung Austin Semiconductor, NXP Semiconductors, and Silicon Labs all run significant Austin data environments. Semiconductor manufacturing data requires connecting MES, SCADA, and ERP systems — handling high-frequency sensor data for yield analysis, equipment OEE, and defect tracking. We have built data platforms that integrate production historian data with financial and planning systems to give leadership a unified view across operations.

How do you architect data platforms for Texas state government?

We understand Texas DIR procurement frameworks, data residency and sovereignty requirements for state data, and how to build data architectures that comply with state security standards. Public sector platforms need to integrate with legacy agency systems, support multiple reporting requirements across legislative and executive stakeholders, and maintain audit trails for transparency requirements.

Can you connect our data architecture to Snowflake, dbt, BigQuery, Databricks?

Yes. Austin's tech ecosystem is built on these tools — and we design the full architecture around them. This means a proper transformation layer (dbt models for certified metrics), a semantic layer on top of the transformation layer, row-level security aligned to your Snowflake or BigQuery access controls, and materialisation strategies that keep performance fast as your data grows.

What is the difference between a data warehouse, a data lake, and a data lakehouse — and which one do we need?

A data warehouse (Snowflake, BigQuery, Synapse) is optimised for structured, query-ready analytics data. A data lake (Azure Data Lake Storage, S3) stores raw data in any format at low cost. A data lakehouse (Databricks with Delta Lake, Snowflake with Iceberg) combines the storage flexibility of a lake with query performance and ACID guarantees. For most Austin tech companies, we recommend a lakehouse architecture on Databricks or Snowflake as the single platform — with dbt transformations and certified data sources serving both your BI and ML teams from the same governed foundation.