Principal Data Engineer

Job Description:

About Dimensional:

Dimensional was built around a set of ideas bigger than the firm itself. With a confidence in markets, deep connections to the academic community, and a focus on implementation, we go where the science leads, and continue to pursue new insights, both large and small, that can benefit our clients.

The Technology Department at Dimensional leverages the rapidly evolving state of the art to engineer scalable, innovative, and research driven solutions to improve our client’s financial lives.

Data Engineers at Dimensional participate in the design and development of data solutions across an array of domains from Research and Investments to Sales and Marketing; collaboratively developing MVPs to test their ideas and rapidly iterate with constant feedback from users. Dimensional invests heavily in developer tools, platforms, paradigms and experience enabling teams to provide modern solutions that contribute profoundly to our client’s success.

We are looking for a Principal Data Engineer to join our team and drive company success by helping Dimensional leverage its critical data. The most important qualifications are a passion for driving business value through quality data solutions and high enthusiasm for learning new technologies and approaches to solving complex business problems

You may be a fit for this role if you:

• Are open-minded, curious, and resourceful

• Are passionate about/stay current with modern technologies

• Solve problems systematically and transparently

• Share ideas, solicit/integrate feedback, design and solve collaboratively

• Take a software engineering approach and demonstrate automation and security mindsets

What you might work on:

As a Principal Data Engineer at Dimensional, you will have the opportunity to understand the users’ needs and solve problems like database and schema design and engineering, ETL pipelines, APIs, and microservice design and engineering.

Key Responsibilities:

• Strategic Architecture: Architect and oversee the engineering of large-scale data warehouses and lakes, specifically utilizing Snowflake for high-concurrency and complex modeling needs.

• Pipeline Orchestration: Design and manage sophisticated data workflows and transformation layers using Airflow and dbt.

• Full-Stack Data Engineering: Write and review high-quality, production-ready code, primarily utilizing Python and JavaScript.

• Data Modeling & Design: Drive the strategy for relational and non-relational database schemas, focusing on performance, scalability, and long-term maintainability.