Senior Data Engineer - Data Platform

Buildertrend • Omaha, NE

1d • $130,000 - $160,000

About The Position

As a Senior Data Engineer on Buildertrend’s Data Platform team, you will lead the migration of its data platform to a modern Databricks lakehouse built on dbt. You will replace legacy systems with a reliable source of truth by designing pipelines that ingest data from systems such as Salesforce, SQL Server, and Gong, and turn it into curated, trustworthy datasets for business teams and AI tools. This work is intended to reduce manual engineering work and establish standards for the platform and its engineers.

You will build and maintain the lakehouse and its ELT pipelines, lead the retirement of legacy systems, and improve ingestion reliability, data quality, monitoring, access controls, privacy handling, and documentation. You will establish data contracts with product engineering and build curated data products. You will partner with data science, machine learning, and AI teams on datasets for models and experiments, and collaborate with engineers, analysts, business leaders, and other stakeholders to deliver platform improvements. You will also mentor engineers, contribute to architecture decisions, evaluate technologies, and grow toward a technical leadership role while using AI thoughtfully.

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 experience with Databricks, including building and orchestrating pipelines, managing jobs and clusters, and using Unity Catalog for governance.
• Production-level hands-on experience with dbt, including building and maintaining models, tests, and macros.
• Proven experience leading a data platform migration, such as moving from a legacy warehouse to a modern lakehouse, 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.
• Experience writing data tests, setting up freshness and alerting monitors, and building access controls or governance policies in a live production environment.
• Strong communication skills, including explaining technical tradeoffs to engineers and non-technical stakeholders, especially during system migrations.
• 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 the Databricks lakehouse using a dbt medallion architecture, and establish layer standards, naming conventions, and build rules.
• Build ELT pipelines with Databricks, dbt, and Fivetran to ingest data from SQL Server, Salesforce, MongoDB, Gong, OpenTelemetry, and vendors such as Zonda, creating curated datasets for analytics and AI.
• Lead the migration away from legacy systems such as BigQuery, Data Fusion, and Cloud Fusion; refactor pipelines, untangle circular dependencies, and repoint tools such as Tableau to the new platform with clear owners and deadlines.
• Improve reliability by strengthening SQL Server log-ship replication and Fivetran ingestion, and building automation such as auto-recovery, full-refresh jobs, and watchdog orchestration.
• 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 through tools such as DataGrail to meet CCPA requirements.
• Set up data contracts with product engineering to prevent upstream schema changes from silently breaking the warehouse.
• Write documentation, including data dictionaries, ERDs, specification documents, and column notes, that is clear to 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.
• Partner 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, plus 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior