Senior Data Engineer

Summary

Join SimplePractice as a Senior Data Engineer to lead the evolution of our data stack, building infrastructure for product intelligence, financial reporting, and self-serve analytics. You will work with various teams to create scalable, reliable systems, enabling accessible insights for clinicians and fueling internal reporting and forecasting. The role involves partnering with Product, Analytics, and Engineering teams, leading technical vision, and managing the complete data stack. You will build tools for transparency in reporting, work with DevOps for deployment, and define data quality and security frameworks. This position offers the opportunity to shape data that directly helps clinicians run more efficient businesses and make smarter decisions.

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)

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 practices

Preferred Qualifications

• 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 Kinesi

Benefits

• Privatized Medical, Dental & Vision Coverage
• Work From Home stipend
• Flexible Time Off (FTO), wellbeing days, paid holidays, and Summer Fridays
• Monthly Meal Reimbursement
• Holiday Bonus, 15-day Aguinaldo
• Hybrid Work Schedule & Catered Lunch
• A relocation bonus for candidates joining us from a different city
• Employee Resource Groups (ERGs)