Build the data foundation behind a growing family of local service businesses.

Landmark Foundation Group (LFG) partners with leading foundation repair, waterproofing, and structural services companies across the country. We help local businesses grow through investments in people, technology, and operations while preserving the leadership, reputation, and customer relationships that made them successful. Learn more about LFG.

We are looking for a hands-on Data Engineer to build and own the pipelines, models, and applications that help our businesses measure performance and make better decisions.

You will connect data from Salesforce, NetSuite, Accutrax, ArcSite, and other operating systems using Snowflake, Fivetran, dbt, and Streamlit, supported by Python-based AWS Lambda functions and Terraform deployment scripts. Working closely with analytics, finance, and operating teams, you will turn fragmented information into reliable datasets and useful business tools.

This is an individual-contributor role with meaningful ownership and room to shape how our data platform grows.

Why Join Landmark

• Own what you build. Take responsibility from source integration through the models and applications people use.
• Work with a modern stack. Build dependable infrastructure and practical tools using current data and development technologies.
• See the impact. Help local and platform leaders understand sales, operations, and financial performance.
• Grow with the business. Establish patterns that support additional brands, systems, and users.

What You’ll Own

• Build and maintain automated ingestion into Snowflake using Fivetran and custom Python integrations running in AWS Lambda.
• Develop tested, documented dbt models that connect customer, sales, job, and financial data across brands.
• Build Streamlit applications for data exploration, reporting, and business workflows.
• Monitor data freshness, completeness, and accuracy; troubleshoot issues and resolve root causes.
• Maintain Terraform deployment scripts and Git-based workflows for repeatable, reviewable changes.
• Optimize Snowflake performance and cost, apply appropriate access controls, and document key models and dependencies.
• Partner with business stakeholders to define consistent metrics and onboard additional brands and systems.

What You Bring

• Approximately 3–6 years of experience in data engineering, analytics engineering, or a related development role.
• Strong SQL and Python, including analytical modeling, REST API integrations, and maintainable application code.
• Hands-on experience with Snowflake, Fivetran, and dbt, or closely comparable tools.
• Experience developing Streamlit applications that business users can navigate and use effectively.
• Familiarity with AWS Lambda, Terraform, and Git-based development and deployment.
• The ability to work independently, prioritize practical solutions, and explain technical decisions clearly.

Experience with Salesforce, NetSuite, Accutrax, or ArcSite is especially helpful. We also value experience using ChatGPT or Claude to build, debug, and improve Python and Streamlit applications, with sound judgment about generated code, accuracy, and company data. Experience embedding AI capabilities into business applications is a plus.

What Success Looks Like

Core systems feed reliable, tested data into Snowflake. Analysts and leaders trust consistent models and metrics. Streamlit applications make information easier to use, manual work decreases, and new brands can join the platform through repeatable integrations.