Senior Database Engineer - Mountlake Terrace, WA

Job Type: Full-time M-F, hybrid options available

Location:

Mountlake Terrace, WA

Pay: $160,000k - $190,000k per year

We are abusiness-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 teamscurrently support over 2,000independentmental 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.

The Senior Database Engineer is responsible for the design, development, and operational ownership of Mindful Support Services' data platform, including databases, data warehouses, and Azure-based data pipelines. Operating with a high degree of autonomy, this role leads the architecture, implementation, and ongoing management of data systems while managing the Database Administrator and Power BI Developer.

This position owns end-to-end data movement and transformation across Microsoft Fabric and Azure environments, leveraging PySpark, T‑SQL, and modern data engineering practices. Responsibilities include building and maintaining resilient data pipelines, overseeing CI/CD processes in Azure Dev Ops, and ensuring the reliability of production-critical data workflows that support both business operations and analytics.

This is a hands‑on technical leadership role for an engineer who is comfortable working independently while leading a team and maintaining critical systems that are essential to daily business operations.

This is a full‑time, in person role based out of our Mountlake Terrace Headquarters, with occasional travel to other MSS locations as needed and Hybrid work schedule available with tenure.

• Design, build, and maintain enterprise‑grade data warehouses within Microsoft Fabric (Warehouse, Lakehouse) using PySpark.
• Implement and manage data models including fact and dimension tables supporting operational and analytical workloads.
• Apply Medallion architecture (Bronze, Silver, Gold) to structure scalable, maintainable data pipelines.
• Optimize storage, query performance, and cost efficiency across Fabric and Azure environments.

• Develop, deploy, and maintain data pipelines using PySpark, SQL, and Azure‑native services to facilitate development across the Dev Ops team.
• Engineer scalable ETL/ELT processes that ingest, transform, and load data across multiple systems.
• Own pipeline reliability, monitoring, alerting, and failure recovery in production environments.
• Troubleshoot and resolve issues across ingestion, transformation, and storage layers with minimal escalation support.

• Design and manage CI/CD pipelines in Azure Dev Ops for database changes, data pipelines, and data models.
• Implement version control, automated deployments, and testing strategies for all data assets.
• Maintain release processes for schema changes, stored procedures, and pipeline updates across environments.

• Write, optimize, and maintain advanced T‑SQL code (stored procedures, views, functions, indexing strategies).
• Perform query tuning and performance optimization across high‑volume transactional and analytical workloads.
• Design and enforce database standards, naming conventions, and documentation practices.

• Lead the Database Administrator in best practices around Data governance, reliability and security.
• Implement role‑based access controls and data security aligned with HIPAA and internal policies.
• Own backup, restore, and disaster recovery strategies for databases and pipelines.
• Conduct regular validation of data integrity and pipeline outputs.

• Partner with analysts, operations, and engineering teams to translate business requirements into scalable data solutions.
• Provide technical guidance on data modeling, pipeline design, and platform best practices.
• Document systems, pipelines, and processes to ensure maintainability despite lean operational support.