Lead Data Engineer: Scale Pipelines & AI-Driven Data

Scaffold; Austin, Northern (TX, KY); Hybrid; USD 130,000 - 170,000; Full time

Benefits offered by this job

Competitive salary

Meaningful equity

On-site in Austin

Job summary

Scaffold in Austin, TX is seeking a Senior Data Engineer to design and build a world-class data architecture and pipeline. You’ll lead the data platform’s scale, accuracy, and performance in an early-stage, venture-backed product.

You’ll architect and maintain pipelines, model large datasets, and collaborate with product and engineering to drive integration flows. Proficiency in Python and SQL is required, with experience in modern tools like Airflow, dbt, Kafka, and Snowflake.

Qualifications

• 5+ years in data engineering or backend engineering.
• Strong Python expertise in production environments.
• Proficiency in SQL, data modeling, and modern data pipelines.
• Airflow, dbt, Kafka, Snowflake experience is a plus.
• Startup mindset with fast-paced, high-ownership environment.
• Strong written and verbal communication skills.

Responsibilities

• Architect, build, and maintain reliable data pipelines and infrastructure.
• Standardize, clean, and model large sets of real-world construction data.
• Develop tools to ensure data quality, accuracy, and performance at scale.
• Partner closely with product, engineering, and customers to design integration flows.
• Apply Python and SQL for ETL workflows.
• Leverage AI/ML methods to improve automation of data classification and mapping.
• Help define best practices for data governance and reliability.

Skills

Python

SQL

Data modeling

AI/ML workflows

Tools

Airflow

dbt

Kafka

Snowflake

Job description

Scaffold in Austin, TX is seeking a Senior Data Engineer to design and build a world-class data architecture and pipeline. You’ll lead the data platform’s scale, accuracy, and performance in an early-stage, venture-backed product.

You’ll architect and maintain pipelines, model large datasets, and collaborate with product and engineering to drive integration flows. Proficiency in Python and SQL is required, with experience in modern tools like Airflow, dbt, Kafka, and Snowflake.