Data Engineer

Lake Flato is seeking a Data Engineer to help build and maintain the firm’s evolving AI infrastructure initiatives. The ideal candidate will work alongside our Systems Integrator to support our office-wide, multi-year Data & AI Initiative, focusing on the buildout of the firm’s Lakehouse as our primary in-house data engineering resource.

About Lake Flato

For more than four decades, Lake Flato has designed buildings and places that respond to climate, culture, craft, and community. A certified B Corp, the firm is recognized for creating environments that are environmentally responsible, deeply contextual, and enduring in their impact. With offices in San Antonio, Austin, and Portland, Lake Flato’s work spans civic, K–12, higher education, residential, urban development, interiors, sustainability, and related markets.

Our Data & AI Initiative

Lake Flato is investing in a multi-year, firm-wide Data & AI initiative to bring modern data infrastructure and AI-powered tools into how we run projects, manage finances, and develop new work. The foundation of that effort is a data Lakehouse, a single, well-governed home for data that consolidates our project management, finance, HR, and design systems.

We are partnering with an external systems integrator to build the initial platform over a focused seven-month engagement, supported by a dedicated IT infrastructure partner who manages our cloud environment, deployment, and operations.

The Role

The Data Engineer will build and maintain the infrastructure that makes the initiative possible. Every piece of data that flows from our systems into a dashboard or an AI tool will pass through pipelines you build. You will work alongside our systems integrator through the seven-month build, contributing to the work while absorbing the architecture, and then carry that infrastructure forward as the firm’s primary in-house data engineering resource once the engagement ends.

This is a foundational, build-from-the-ground-up role with unusual ownership. You will report to the Data & AI Lead and work closely with the integrator team, our IT infrastructure partner, and colleagues who specify the tools the firm needs. Cloud infrastructure, deployment, and CI/CD are owned by our IT infrastructure partner, so this is a focused data-engineering role, not a platform-operation one, and you can put your attention on building reliable, well-documented data pipelines.

Responsibilities:

Building the Lakehouse

·      Build the Lakehouse pipeline using automated ingestion pipelines that pull data from our project management/ERP system, HR systems, design and BIM tools, and CRM on a scheduled basis.

• Build the Bronze layer—a raw, unmodified copy of source data that preserves the original as it is transformed downstream.
• Build the Silver layer—cleaned and standardized data: removing duplicates, standardizing fields, handling missing values, and joining related datasets across systems.
• Build the Gold layer—business-ready, aggregated datasets structured for specific use cases such as project profitability, utilization analytics, and fee benchmarking.
• Develop the serving layer and API integrations that connect Gold data to dashboards and AI applications.

Owning the system’s quality

• Monitor pipeline health on a regular cadence and resolve failures, data anomalies, and feed disruptions.
• Maintain data lineage documentation so any output can be traced back to its source.
• Apply the firm’s data quality and governance standards—surfacing issues rather than masking them.
• Add new data sources and extend transformation logic as the initiative grows.

Internalize and document the architecture

• Work alongside the systems integrator during the build, treating every session as a chance to understand why architectural decisions are made—not just what to build.
• Produce clear documentation alongside the build, including plain-language runbooks that let others maintain and extend the system.
• By the end of the engagement, be able to add sources, modify logic, and troubleshoot failures independently.

Required Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field—or equivalent practical experience.
• 4+ years of hands-on data engineering experience building and maintaining production data pipelines (ingestion, transformation, and scheduled automation).
• Strong proficiency in Python and SQL.
• Working experience with a cloud data environment—Microsoft Azure preferred; AWS or GCP experience readily transferable.
• Familiarity with layered or medallion data architecture patterns (Bronze/Silver/Gold or equivalent staged transformation models).
• Experience integrating data from REST APIs and enterprise systems (ERP, finance, HR, or similar).
• Demonstrated discipline in documentation—you write things down so others can maintain what you build.

Preferred Qualifications

• Experience with platforms such as Databricks, Azure Synapse, or Microsoft Fabric.
• Exposure to an architecture, engineering, or professional-services ERP system (e.g., Deltek VantagePoint) or comparable project-based financial systems.
• Understanding of data governance practice—cataloguing, access controls, lineage, and quality standards.
• Experience building serving layers or APIs that feed dashboards and applications.
• AI-adjacent data engineering: experience standing up and maintaining vector stores and embedding pipelines, and serving curated data to LLM or AI applications through APIs.
• Interest in how data infrastructure connects to analytics and AI—not just moving data, but enabling what it powers.
• Experience working alongside an external systems integrator or consulting team and carrying a system forward independently afterward.

Details

• Permanent, full-time position based in our San Antonio office, with on-site presence expected during the implementation engagement and a hybrid schedule thereafter.
• Competitive compensation, commensurate with experience.
• Target start: late July 2026.

Application

Please send a digital copy of the required information below by e-mail to lfhr@lakeflato.com.

• Format email with subject line ‘Data Engineer’
• Resume & Cover Letter

When applying, please include responses to the following questions in your email:

• How did you hear about Lake Flato?
• Are you legally authorized to work in the U.S.?
• Will you now or in the future require sponsorship for employment visa status?
• Can you perform the essential functions of the job for which you are applying, with or without reasonable accommodation?
• What date are you available to start working?
• What are your salary requirements?

Please visit our website at www.lakeflato.com for more information on our firm, our culture and our people. Upon receipt, we will review and contact you should your qualifications meet our staffing needs. No phone calls, please.