Data Engineer

• Lead migration of the data platform to a modern Databricks lakehouse built on dbt
• Design, build and maintain the Databricks lakehouse using medallion architecture
• Set layer standards, naming conventions and build rules for other engineers
• Build ELT pipelines with Databricks, dbt and Fivetran from SQL Server, Salesforce, MongoDB, Gong, OpenTelemetry and vendors such as Zonda
• Lead the exit from legacy systems including BigQuery, Data Fusion and Cloud Fusion
• Refactor pipelines, untangle circular dependencies and repoint Tableau to the new platform
• Improve SQL Server log-ship replication and Fivetran ingestion
• Build 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, 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
• Establish data contracts with product engineering and write data dictionaries, ERDs, specifications and column notes
• Build and improve curated data products for stakeholders and customers
• Partner with data science, machine learning and AI teams on datasets for models and experiments
• Partner with engineers, analysts, business leaders and stakeholders to prioritize work, manage dependencies and deliver platform improvements
• Mentor engineers, contribute to architectural decisions, evaluate emerging technologies and develop toward technical leadership

Explore Senior Data Engineer – Data Platform at Buildertrend. Review requirements and application details.