Data & Integration Engineer

Weekly outpatient therapy isn't always enough, and a trip to the ER isn't the only answer. Patients and their families rely on Compass Health Center when in crisis – every day, we help people overcome depression, anxiety, suicidality, obsessions/compulsions, trauma, chronic pain, and other obstacles in order for our patients to live freely.
About This Role
The Data & Integration Engineer is a hands-on technical role responsible for building and maintaining Compass Health Center's data platform, integrations, pipelines, and trusted data foundation. In this role, you’ll play an important part in connecting data across clinical, operational, financial, and business systems, ensuring it is reliable, secure, well-structured, and accessible to support reporting, analytics, and AI-enabled use.
You’ll help shape and strengthen Compass's data environment by centralizing and standardizing data, reducing manual and fragile processes, and building scalable solutions using Microsoft Fabric and related technologies.
Our dedicated operations teams work behind the scenes to bring our shared mission to life. Each department delivers their own set of strengths which empower our clinicians to focus on their expertise, and ultimately perform the meaningful work that we do.
What You'll Do
Data Engineering & Integration
Build, maintain, and improve data pipelines, integrations, transformations, lakehouse structures, and data models.
Bring data from EMR/EHR, finance, HR, CRM, scheduling, payer, and other systems into a governed data platform.
Use SQL, Python/PySpark, APIs, dataflows, notebooks, connectors, gateways, and other appropriate tools to move and transform data.
Replace manual, file-based, or fragile processes with reliable and scalable solutions.
Build integrations between cloud based, and SaaS systems.
Evaluate new data sources and determine the best approach for ingestion, integration, and ongoing support.
Reliability, Quality & Security
Monitor pipelines, refreshes, integrations, and data quality and quickly troubleshoot failures.
Build appropriate logging, alerting, error handling, and recovery processes.
Resolve issues related to source-system changes, schemas, credentials, gateways, and data availability.
Improve the reliability, performance, and maintainability of existing data workflows.
Reduce dependencies on individual users, workstations, manual file movement, and undocumented processes.
Maintain clear documentation, lineage, naming standards, and technical ownership of data assets.
Support appropriate data access, security, privacy, and handling of PHI and other sensitive information.
Analytics & AI Enablement
Build the trusted data foundation needed for reporting, self-service analytics, and AI-enabled analysis.

Skills
Python, SQL, CRM, Documentation