Senior Data Engineer

SimplePractice is a company focused on improving access to quality care for health and wellness clinicians. They are seeking a Senior Data Engineer to lead the evolution of their data stack, building infrastructure that powers product intelligence, financial reporting, and self-serve analytics, ultimately helping clinicians run more efficient practices.

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

Requirements:

• 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
• 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
• Experience with AWS (S3, RDS, Redshift, etc.)
• Skilled in handling structured, semi-structured (e.g., JSON), and columnar formats (e.g., Parquet, ORC)
• 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
• Proficient in Python and Unix/Linux scripting
• Comfortable working with APIs (e.g., using curl)
• Familiar with Terraform, Docker, and containerized workflows (bonus)
• 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