Sr Analytics Engineer (Remote)

As a Sr Analytics Engineer at Rula, your primary responsibilities include designing and implementing trusted, scalable data models that support decision-making company-wide. You will work intensively with dbt, Redshift, and Looker, collaborating with cross-functional teams to create data solutions that address complex queries. Your role will also involve performance tuning and optimizing queries within a cloud data warehouse, ensuring that our analytics framework remains efficient and impactful.

To apply for the Sr Analytics Engineer role at Rula, you’ll need a Bachelor's degree in Computer Science or Data Science, coupled with 3-5 years of experience in analytics engineering or similar fields. Key qualifications include advanced proficiency with dbt and strong SQL skills, particularly in crafting Kimball-style dimensional models. Experience with AWS tools, especially Amazon Redshift, and BI solutions like Looker is critical as well.

Rula is committed to promoting a healthy work-life balance for its Sr Analytics Engineers by offering a 100% remote work environment. This means flexibility in working hours to accommodate personal commitments, along with generous time-off policies that include company-wide shutdown weeks for self-care. Here, we understand that great work comes from a well-balanced life.

In your role as a Sr Analytics Engineer at Rula, you'll utilize a suite of powerful tools, including dbt for data transformation, Amazon Redshift as the cloud data warehouse, and Looker for business intelligence. You'll be involved in designing clean, modular data transformations and developing insightful dashboards to aid in decision-making processes across the company.

While not strictly required, prior experience in a healthcare or regulated data environment is preferred for the Sr Analytics Engineer position at Rula. Familiarity with HIPAA regulations and understanding of privacy considerations in analytics are valuable assets that will help you navigate our mission-driven landscape effectively.

In responding to this question, detail a specific project where you designed a complex data model, focusing on your process, the tools you used, and the impact it had. Highlight any challenges you faced and how you overcame them, particularly emphasizing your skills with dbt and SQL.

Share specific techniques you've used to enhance performance, such as indexing, consolidating data, or refining SQL queries. Discuss the results of these improvements, providing metrics if possible, to demonstrate your impact in a cloud environment like Amazon Redshift.

Discuss the principles of modular design that you adhere to, such as creating well-documented transformation layers and avoiding one-off analyses. Mention specific documentation practices and organizational tools that you utilize to promote knowledge sharing and reusability.

Provide an example of a project where you had to simplify complex insights. Highlight the methods you utilized to present your findings clearly, such as using visualizations, analogies, or the management of dashboards in Looker, ensuring you catered to the audience's level of understanding.

Share your hands-on experiences with Looker, detailing any dashboards you created and the metrics they tracked. Discuss specific features of Looker you leveraged, such as LookML, to build complex data explorations that informed company decisions.

Talk about your experience with integrating Continuous Integration and Continuous Deployment in analytics workflows, specifically how you apply CI/CD principles within tools like dbt and Git to maintain code quality and streamline deployment processes.

Touch on your time management skills and collaboration strategies that help you juggle multiple projects. Illustrate an example of how you coordinated with different teams, what tools you used (like project management tools), and how you ensured deadlines were met without compromising quality.

Discuss specific challenges, such as data privacy concerns or navigating compliance protocols like HIPAA. Explain the strategies you implemented to ensure data integrity while facilitating analysis, demonstrating your problem-solving abilities in a regulated environment.

Share your perspective on the importance of well-being, especially in a mission-driven environment like Rula’s. Connect your personal values to the company’s mission, illustrating how a healthy workforce enhances productivity and engagement in data-driven decision-making processes.

Highlight skills critical to the role, such as technical aptitude with data tools, creativity in problem-solving, and empathy towards stakeholders' needs. Discuss how these skills can contribute to developing effective data solutions that support Rula's mission in transforming mental health care.