Who We Are
Stratus Data is a consultancy that enables industry leaders to solve their most pressing challenges using data science. We’ve collaborated with research teams at top institutions like Harvard and Stanford, as well as at companies like General Electric and 21st Century Fox. Our past projects include:
- Data Infrastructure
- Business Intelligence
- Machine Learning
- Medical Devices
We are remote-first, with a strong presence in the San Francisco Bay Area.
Who You Are
Stratus Data is looking for a Senior Analytics Engineer with 7+ years of applied data experience to join us in driving organizational impact. The candidate will be responsible for designing data marts, developing data pipelines using SQL with transformation tools like DBT, creating proof of concept dashboards to demonstrate the pipelines, and communicating the results to both technical and executive audiences. The ideal candidate possesses strong situational and interpersonal awareness, an understanding of the business context they operate in, a tireless pursuit to grow, and a curiosity for the “why” beyond the “what”. Integrity and fast thinking are a must. Most of all: empathy. Our job is to marry organizational challenges to data science solutions.
What You’ll Do
- Architecture and Usability Engineering: design and implement the right tools, technologies, and processes to serve the needs of a data organization.
- Data Modeling and Analytics Engineering: design scalable data models that transform raw data to consumption-ready data for analytical and business audiences. Develop efficient and robust data pipelines that support the data models you design.
- Communicating: synthesize technical developments and key findings to inform executive decision making at clients.
- Teaching and Learning: develop curricula and content that enable the Stratus team to grow through what you learn.
What You’ll Bring
- Bachelor’s or Advanced Degree in Engineering, Applied Math, Science, or equivalent.
- 7+ years of applied data or analytics engineering experience.
- Expertise in SQL.
- Fluency in designing and implementing data warehouses.
- Proficiency in Python.
- Proficiency in visualization software.
- Extreme thoroughness and attention to detail.
- Ability to communicate complex subjects to technical and non-technical audiences.
- Strong orientation towards collaboration and enabling peer growth.
- Experience with software engineering.