Employment Status: Full-Time
Location: Remote (U.S.)
Schedule: Standard business hours with occasional evenings/weekends as needed
Salary Range: $100,000 - $120,000
A rapidly growing, multi-site consumer services organization is seeking a Data Engineer to own customer/member data, core KPIs, and the underlying data infrastructure that supports analytics and marketing workflows.
This role sits between analytics engineering and data engineering, with a strong emphasis on data accuracy, reliability, and trust. The data environment directly supports executive KPI dashboards and customer engagement workflows, where incorrect data can materially impact business operations and customer experience.
A significant portion of this role focuses on CRM and lifecycle data, including customer attributes, segmentation, and targeting logic. While not responsible for building dashboards or campaigns, this role owns the data that powers them.
The ideal candidate brings strong experience in SQL, data modeling, and modern data stack tools, along with a clear understanding of how marketing and CRM systems consume data in production environments.
• Own and maintain the customer/member data environment, including the health and reliability of key data integrations
• Define, model, and manage customer attributes and core KPIs used across the organization
• Ensure the accuracy, consistency, and reliability of data supporting dashboards and customer engagement workflows
• Design, build, and maintain data integrations and ingestion pipelines supporting CRM and lifecycle use cases
• Develop and maintain analytics-ready data models for long-term metric stability
• Build and manage automated testing, validation, and data quality safeguards
• Enforce system-level data validation to ensure only trusted data reaches downstream systems
• Own data incidents from detection through resolution, including stakeholder communication
• Contribute to ETL pipelines using dbt, Airflow, and Python-based processes
• Support API-based data ingestion and enrichment initiatives
• Collaborate with analysts and business stakeholders on data definitions and usage