Database Engineer - Mountlake Terrace, WA

Job Type: Full time, M-F

Location: Mountlake Terrace, Wa, hybrid options available

Salary: $110,000 - $140,000, DOE

About Mindful Support Services

We are a business-to-business support service for independent mental healthcare businesses, which helps providers service a growing client base. We provide administrative and organizational services to simplify the processes of lead-generation, marketing, billing, and collecting payments from patients and insurers. Our teams currently support over 2,000 independent mental health providers, who serve over 25,000 clients per week across 20+ locations throughout 5 states, as well as virtually via Telehealth.

We have built the Mindful Therapy Group brand from the ground up with years of dedication to solving the complex processes of the mental healthcare landscape in innovative ways, creating a platform geared toward growth, and working to meet our mission of creating improved access to high quality mental healthcare.

About the Role

As the Database Engineer, you will serve as a technical generalist and problem-solver across departments and business units. Reporting to the Director of Operations, you will partner with the Operations Team and other internal stakeholders to investigate business challenges and design and deliver custom solutions that support operational success. You will develop tools to optimize workflows, integrate systems, and manage data pipelines across internal and vendor-supported initiatives, while maintaining clear documentation and consistent process standards.

This is a full-time, hybrid position based at our Mountlake Terrace Headquarters, with travel to other Mindful Support Services locations as needed.

Work Environment

This is an hybrid based at our Mountlake Terrace Headquarters. Off-site travel may also be needed to support projects, equipment setup, or vendor coordination.

The responsibilities listed above are not exhaustive. Duties and responsibilities may evolve over time with or without formal notice.

Responsibilities

Database & Fabric Development

• Develop, maintain, and troubleshoot data solutions primarily within Microsoft Fabric.
• Provide limited support for existing SQL Server environments.
• Work under the technical guidance of the Senior Database Engineer and follow established engineering standards.

Data Engineering & Integration

• Develop and maintain ETL/ELT pipelines, Fabric notebooks, and data integration processes using SQL and PySpark.
• Ingest, transform, and integrate data from operational systems, databases, and APIs.
• Support existing Azure-based integrations and data workflows as needed.

Data Warehousing & Data Modeling

• Build and maintain Microsoft Fabric Lakehouse and Warehouse solutions.
• Design and support Bronze, Silver, and Gold data layers, including fact tables, dimension tables, SQL queries, and transformation logic.
• Collaborate with BI and reporting teams to implement Gold-layer business rules and reporting requirements.

Production Support & Optimization

• Monitor pipelines, notebooks, data refreshes, and scheduled jobs.
• Investigate failures, troubleshoot performance issues, and implement routine fixes.
• Escalate complex issues and participate in ongoing platform optimization efforts.

Source Control & Deployment

• Utilize Git and Azure DevOps for source control, pull requests, code reviews, and testing activities.
• Participate in CI/CD processes and production deployments following established release management standards.

Data Quality & Governance

• Implement data validation, reconciliation, and source-to-target quality checks.
• Investigate data discrepancies and verify transformation accuracy.
• Adhere to established data governance, security, and compliance standards.

Project Delivery & Documentation

• Scope assigned work with the Senior Database Engineer and provide effort estimates.
• Communicate project status, dependencies, risks, and blockers in a timely manner.
• Maintain technical documentation, source-to-target mappings, data dictionaries, and operational runbooks.
• Collaborate cross-functionally to deliver reliable, scalable, and well-documented data solutions.