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# Senior Data Engineer

- **Company:** SimplePractice, LLC.
- **Location:** Santa Monica, CA, United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** AI Evaluation, Agile Methodology, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Cloud Computing, Databases, Directed Acyclic Graph (Directed Graphs), Information Engineering, Extract Transform Load (ETL), Data Warehousing, DevOps, Dimensional Modeling, JSON, Python (Programming Language), Performance Tuning, Scrum Methodology, SQL Databases, Data Streaming, Tableau (Software), Parquet, Scripting, Snowflake, Backend, Data Layers, Core Data, Kubernetes, Information Technology, Data Analytics, Apache Kafka, Build Tools, Api Design, Terraform, Looker Analytics, Docker
- **Published:** October 16, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88120375/1

## About the Role

+ 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

## Description

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