> Markdown version of [/jobs/ext/2636011-senior-data-engineer](https://www.wearedevelopers.com/jobs/ext/2636011-senior-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Buildertrend Solutions, Inc. - **Location:** Omaha, NE, United States (Remote available) - **Experience:** Expert - **Salary:** $130,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Big Data, BigQuery, Cloud Computing, Data Validation, Data Dictionary, Information Engineering, Data Fusion, Data Infrastructure, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Microsoft SQL Server, MongoDB, Raw Data, Salesforce.Com, Software Engineering, SQL Databases, Tableau (Software), Buildertrend Software, Snowflake, Information Technology, Data Analytics, Api Design, Data Pipelines, Legacy Systems, Databricks - **Published:** August 10, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6a0d83ad41e4c629 ## About the Role * 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. * Previous experience at a B2B SaaS company is preferred. * 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. Experience with BigQuery, Snowflake and Fivetran is a plus. * 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. ## Description As a Senior Data Engineer at Buildertrend, you'll lead the migration of our data platform onto a modern Databricks lakehouse, replacing today's patchwork of legacy systems with a single, reliable source of truth. You'll design the pipelines that bring in data from tools like Salesforce, SQL Server and Gong, turning it into curated, trustworthy datasets that teams across the business, and the AI tools built on top of them, can rely on without double-checking the numbers. Your work directly cuts down on the manual firefighting that eats into engineering time today, and sets the technical standards other engineers will build on for years. By the end of your first year, you'll have carried a major legacy system migration to completion and be stepping into a mentorship or leadership role on the team. What you will do: * 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [40 Minutes to Build a Serverless COVID-19 REST and GraphQL APIs](https://www.wearedevelopers.com/videos/208-40-minutes-to-build-a-serverless-covid-19-rest-and-graphql-apis) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Making Data Warehouses fast. 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