Senior Data Engineer

About Us

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, and BuiltIn'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 lead the evolution of our Marketing Sciences data ecosystem. In this role, you will be the technical architect of the infrastructure that powers our growth engine—from performance marketing attribution to the productionalization of predictive models.

You will bridge the gap between core data engineering and high-impact growth initiatives. While our Data Science team focuses on R&D, you will ensure the high-fidelity customer signals required for Next Best Action (NBA) frameworks, Predictive Lifetime Value (pLTV) models, and Demand Modeling are accurate, scalable, and readily available for the Growth Analytics team.

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 working with APIs (e.g., using curl)
• Bonus Points
• AWS DevOps - Terraform, Kubernetes, Docker
• Project & Change Management skills especially experience working in an Agile (SCRUM, Kanban) environment/team focusing on sprint by sprint deliveries
• Real-time ETL - Kafka streaming, AWS Kinesis