Senior Data Engineer

Buildertrend is a residential construction management platform that helps contractors manage financials, schedules, workflows, and client relationships in one system. The Senior Data Engineer will lead the migration to a Databricks lakehouse, build reliable ELT pipelines and curated datasets, improve data quality and governance, and mentor engineers while advancing toward technical leadership.

Responsibilities:

• Design, build and maintain Buildertrend's Databricks lakehouse using a medallion (bronze, silver, gold) architecture in dbt, and set the layer standards, naming conventions and build rules other engineers follow
• Build ELT pipelines with Databricks, dbt and Fivetran that bring in data from SQL Server, Salesforce, MongoDB, Gong, OpenTelemetry and vendors like Zonda, turning it into curated, analytics- and AI-ready datasets
• Lead the exit from legacy systems like BigQuery, Data Fusion and Cloud Fusion by refactoring pipelines rather than copying them over as-is, untangling circular dependencies, and repointing tools like Tableau to the new platform with clear owners and deadlines
• Strengthen reliability by improving SQL Server log-ship replication and Fivetran ingestion, and by building automation like auto-recovery, full-refresh jobs and watchdog orchestration that cuts down on manual fixes and outages
• Build data quality checks, freshness monitoring and quality metrics using dbt tests, Unity Catalog and Fivetran metadata, so stakeholders can trust the numbers without double-checking them
• Design access controls for large datasets, including permission models, per-team clusters, service principals and scoped access for AI tools, and handle privacy requests through tools like DataGrail to meet CCPA requirements
• Set up data contracts with product engineering so upstream schema changes don't silently break the warehouse, and write documentation (data dictionary, ERDs, spec docs, column notes) clear enough for people and AI tools to use
• Build and improve the curated data products that let stakeholders and customers turn raw data into decisions
• Partner with engineers, analysts, business leaders and other stakeholders to prioritize work, manage dependencies and deliver meaningful platform improvements
• Mentor other engineers, contribute to architectural decisions, evaluate emerging technologies and grow toward a technical leadership role while using AI thoughtfully to improve productivity and engineering outcomes

Requirements:

• Bachelor's degree in computer science, software engineering or a related field is required
• 5+ years of experience in data engineering, data science or data analytics
• Proven experience leading a data platform migration, such as moving off a legacy warehouse onto a modern lakehouse, from planning through delivery, including setting deadlines and owning the outcome
• Experience partnering with Data Science, ML, or AI teams, including building and curating datasets to support model development and experimentation
• Hands-on experience with Databricks, Unity Catalog and dbt
• Strong proficiency in SQL, Microsoft SQL Server, Python and working with APIs and large, complex datasets
• Deep understanding of data modeling, ETL and ELT pipelines, medallion architecture and building analytics and machine learning-ready datasets
• Experience writing data tests, setting up freshness and alerting monitors, and building access controls or governance policies in a live production environment (not just in a sandbox or one-off project)
• Strong communication skills, with the ability to explain technical tradeoffs to both engineers and non-technical stakeholders, especially during a system migration where people need clear, direct answers about what's changing and when
• Demonstrated experience mentoring engineers, reviewing technical work and influencing engineering standards, with an interest in growing into a leadership role
• A practical approach to new tools and technologies, including AI: willing to try things that solve a real problem, but not inclined to chase every new release just because it's new
• Previous experience at a B2B SaaS company is preferred
• Experience with BigQuery, Snowflake and Fivetran is a plus