Senior Data Engineer

About Us SimplePractice is headquartered in Los Angeles, California, but we have team members who work and live across the United States, Dominican Republic, Mexico City, and Ukraine. At SimplePractice, we are improving access to quality care by equipping health and wellness clinicians with all the tools they need to thrive in private practice. More than 250,000 providers trust SimplePractice to build their business through our industry-leading software with powerful tools that simplify every part of practice management. From admin work to clinical care, our suite of innovative solutions work together to reduce administrative burden-empowering solo and small group practitioners to thrive alongside their clients. Award-winning and people-first, SimplePractice is shaping the future of health tech. Recognized by MedTech Breakthrough, the Digital Health Awards, Best Places to Code in Mexico and Built In's Best Places to Work. Our Culture At SimplePractice, culture is our foundation. It influences the way we work, how we serve our customers, and how we approach accomplishing our mission. We have five core values that we strive to embody every day: We think big We take simplicity seriously We come as we are We act with humility We are built on trust Culture is everyone's responsibility at SimplePractice. Our culture is what drives us to do better for our teammates and customers. Connection and collaboration are also key to our success. You will work with our talented multi-national teams and have opportunities to participate in onsites in both the US and Mexico. The Role We're looking for a Senior Data Engineer to help lead the evolution of our data stack-from pipelines to platform. In this role, you'll build the infrastructure that powers everything from product intelligence to financial reporting and self-serve analytics in product Our customers are clinicians in small to mid-sized private practices, and the data you shape will directly help them run more efficient, effective businesses. By enabling accessible insights-from no-show trends to client engagement-you'll give practitioners the tools to make smarter, faster decisions about how they manage care. Internally, your work will fuel everything from executive reporting and revenue forecasting to product analytics and AI evaluation loops. You'll collaborate across Data Analytics, ML, Product, and Engineering teams to build scalable, reliable systems that make data a first-class product at SimplePractice. Responsibilities Partner with Product, Analytics and Engineering to build scalable systems that help unlock the value of data from a wide range of sources such as backend databases, event streams, and marketing platforms Lead technical vision and architecture with holistic point of view on both short-term and long-term horizons Work with analytics to create company wide alignment through standardized metrics across the company Work with Product and Engineering teams to support internal use cases such as financial reporting, product analytics and operational metrics Enable external use cases like customer-facing dashboard, self-serve analytics, and next best action in product Manage the complete data stack from ingestion through data consumption Build tools to increase transparency in reporting company wide business outcomes Work with DevOps to deploy and maintain data solutions leveraging cloud data technologies, preferably in AWS Help define data quality and data security framework to measure and monitor data quality across the enterprise. Define and promote data engineering best practice Desired Skills & Experience Education & Experience BS/MS in Engineering, Computer Science, Mathematics, or related field 7+ years in Data or Analytics Engineering Strong problem-solving and communication skills; comfortable in fast-paced, cross-functional environments Data Engineering & Pipelines Enterprise architecture and enterprise data architecture (data modeling and enterprise dimensional modeling) Expert in SQL and data modeling (relational, dimensional, semantic) Proven experience in data warehouse design, implementation, and maintenance (Snowflake) Hands-on with DBT for modular, testable transformations Experience with orchestration and ingestion tools: Airflow, Prefect, Airbyte, Fivetran, Kafka Familiar with ELT, schema-on-read, DAGs, and performance optimization Cloud & Infrastructure Experience with AWS (S3, RDS, Redshift, etc.) Familiar with Terraform, Docker, and containerized workflows (bonus) Skilled in handling structured, semi-structured (e.g., JSON), and columnar formats (e.g., Parquet, ORC) Analytics & Enablement Experience building and supporting semantic layers for self-serve analytics Proficient with BI tools like Looker, Tableau, or Sisense Comfortable standardizing metrics and enabling trusted, consistent access to data Programming & Scripting Proficient in Python and Unix/Linux scripting Comfortable #J-18808-Ljbffr simplepractice55