Senior Data Engineer - Data Platform
About The Position
As a Senior Data Engineer on Buildertrend’s Data Platform, you will lead the migration of the company’s data platform to a modern Databricks lakehouse built on dbt, replacing legacy systems with a reliable source of truth. You will design pipelines that ingest data from sources such as Salesforce, SQL Server, and Gong, and transform it into curated datasets that business teams and AI tools can use confidently. The role aims to reduce manual engineering work and establish technical standards for the broader engineering team. You will build and maintain a medallion-architecture lakehouse, lead migration away from legacy systems, improve pipeline reliability and data quality, and establish governance, access controls, privacy processes, data contracts, and documentation. You will also develop curated data products and partner with data science, machine learning, and AI teams on datasets for models and experiments. The position includes collaboration with engineers, analysts, business leaders, and other stakeholders, as well as mentoring engineers and contributing to architectural and technical leadership decisions. The position is available remotely in the United States or in a hybrid arrangement in Omaha, Nebraska. Compensation is $130,000–$160,000 per year.
Requirements
- Bachelor’s degree in computer science, software engineering, or a related field.
- At least 5 years of experience in data engineering, data science, or data analytics.
- Production-level, hands-on Databricks experience, including building and orchestrating pipelines, managing jobs and clusters, and using Unity Catalog for governance.
- Production-level, hands-on dbt experience, including building and maintaining models, tests, and macros.
- Proven experience leading a data platform migration from planning through delivery, including setting deadlines and owning the outcome.
- Experience partnering with data science, machine learning, or AI teams to build and curate datasets for model development and experimentation.
- Strong proficiency in SQL, Microsoft SQL Server, Python, APIs, and large, complex datasets.
- Deep understanding of data modeling, ETL and ELT pipelines, medallion architecture, and building analytics- and machine-learning-ready datasets.
- Production experience writing data tests, establishing freshness and alerting monitors, and building access controls or governance policies.
- Strong communication skills, including the ability to explain technical tradeoffs to technical and non-technical stakeholders during a system migration.
- Demonstrated experience mentoring engineers, reviewing technical work, and influencing engineering standards.
Nice To Haves
- Previous experience at a B2B SaaS company.
- BigQuery or Fivetran experience.
Responsibilities
- Design, build, and maintain Buildertrend’s Databricks lakehouse using dbt and a bronze, silver, and gold medallion architecture; establish layer standards, naming conventions, and build rules.
- Build ELT pipelines using Databricks, dbt, and Fivetran to ingest data from SQL Server, Salesforce, MongoDB, Gong, OpenTelemetry, and vendors such as Zonda, and produce curated analytics- and AI-ready datasets.
- Lead the migration away from legacy systems such as BigQuery, Data Fusion, and Cloud Fusion by refactoring pipelines, resolving circular dependencies, and repointing tools such as Tableau to the new platform with clear owners and deadlines.
- Improve reliability of SQL Server log-ship replication and Fivetran ingestion; build automation such as auto-recovery, full-refresh jobs, and watchdog orchestration to reduce manual fixes and outages.
- Build data quality checks, freshness monitoring, and quality metrics using dbt tests, Unity Catalog, and Fivetran metadata.
- Design access controls for large datasets, including permission models, per-team clusters, service principals, and scoped access for AI tools; handle privacy requests using tools such as DataGrail to meet CCPA requirements.
- Establish data contracts with product engineering to prevent upstream schema changes from silently breaking the warehouse.
- Write and maintain documentation, including data dictionaries, ERDs, specification documents, and column notes, that is usable by people and AI tools.
- Build and improve curated data products that help stakeholders and customers turn raw data into decisions.
- Partner with data science, machine learning, and AI teams to build and curate datasets for models and experiments.
- Collaborate with engineers, analysts, business leaders, and other stakeholders to prioritize work, manage dependencies, and deliver platform improvements.
- Mentor engineers, contribute to architectural decisions, evaluate emerging technologies, and use AI thoughtfully to improve productivity and engineering outcomes.
Benefits
- Medical, dental, and vision coverage.
- Life insurance and short- and long-term disability benefits.
- 401(k) plan with Buildertrend matching contributions.
- Generous paid time off, 11 paid holidays, and personal days.
- Parental leave and paid sabbaticals.
- Volunteer time off.
- Wellness program and onsite fitness center.
- Hybrid or remote work opportunities.
- Technology reimbursement for work-from-home technology costs.
- Free daily lunches at the headquarters office and monthly team events.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
