``` Resilience Lab, founded in 2019, is the largest community of clinicians innovating mental health care. Our diverse team of top-tier therapists strives to deliver holistic, high-quality, and affordable care. With technology at its core, Resilience Lab automates non-clinical tasks, fostering strong therapeutic alliances and team-based care, all supported by the Resilience Institute's continuous learning platform.

We are looking for a Senior Data Engineer to join our US-based, fully remote Technology department. This role offers a compensation range of $145k - $175k. As a Senior Data Engineer, you will help grow our data platform, manage our data model, and maintain our data warehouse. Your daily tasks will involve data ingestion, evolving data marts, building new features, and collaborating across teams to solve impactful problems.

If you are aligned with our mission and values, this guide will help prepare you for the interview process. Let's get started with Interview Query! ```

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Resilience Lab as a Senior Data Engineer. Whether you were contacted by a Resilience Lab recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Resilience Lab Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Resilience Lab hiring manager may be present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions. The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Senior Data Engineer role at Resilience Lab usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around the company's data systems, ETL pipelines, and SQL queries.

In the case of data engineering roles, take-home assignments regarding designing data models, building data pipelines, and data warehousing are incorporated. Apart from these, your proficiency in Python scripting, cloud services like AWS, and tools like dbt, Fivetran, and Prefect may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Resilience Lab office or virtually if applicable. Your technical prowess, including programming and data modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Senior Data Engineer role at Resilience Lab.

Quick Tips For Resilience Lab Senior Data Engineer Interviews

• Focus on ELT Data Pipelines: The interview will heavily stress your expertise in writing scalable SQL and working with tools like dbt and Fivetran. Be prepared to showcase your skills with examples from your past experiences.
• Understand Kimball Dimensional Modeling: A strong understanding of data warehousing concepts, especially Kimball dimensional modeling, will set you apart. Brush up on these principles and be ready to discuss how you have implemented them in the past.
• Emphasize Your Collaboration Skills: The role requires frequent collaboration with colleagues across Technology, Product, and Business Intelligence. Highlighting your ability to work in a team environment and communicate effectively will be crucial.

Typically, interviews at Resilience Lab vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

• Create a function moving_window to find the moving window average of a list of numbers. Given a list of numbers nums and an integer window_size, write a function moving_window to find the moving window average.

• When would you use a bagging algorithm versus a boosting algorithm? If comparing two machine learning algorithms, in which scenarios would you prefer a bagging algorithm over a boosting algorithm? Provide examples of the tradeoffs between the two.

• What are the assumptions of linear regression? List and explain the key assumptions that must be met for linear regression to be valid.

What is the average salary for a Data Engineer at Resilience Lab?

Q: What is Resilience Lab's mission and vision?
Resilience Lab aims to improve mental health access and outcomes by connecting clients with a diverse team of best-in-class therapists who provide holistic, evidence-based, high-quality, and affordable care. Our therapists are continuously trained through the Resilience Institute, ensuring the highest quality of service.

Q: What does the Senior Data Engineer role entail?
As a Senior Data Engineer at Resilience Lab, you will be instrumental in establishing and managing our data model and data warehouse. Your responsibilities will include ingesting new data sources, evolving data marts, and building new features for our application platform. You'll collaborate with various teams to design impactful technical solutions, monitor job performance, and fix job failures.

Q: What technical skills are required for the Senior Data Engineer position?
You'll need expertise in writing scalable SQL, a strong understanding of Kimball dimensional modeling, and experience in applying software engineering principles. Proficiency in Python for building data pipelines, experience using dbt in an enterprise setting, and familiarity with AWS are also crucial. Experience with healthtech or US healthcare data will set you apart.

Q: What is the compensation and benefits package for this role?
The Senior Data Engineer position offers a competitive salary ranging from $145k to $175k. Resilience Lab provides a lucrative benefits package including medical, dental, optical coverage, 401k, and more. The role is fully remote, allowing you to work from anywhere in the US while being part of a supportive and inclusive team.

Q: How can I prepare for an interview with Resilience Lab?
To prepare, familiarize yourself with our mission, vision, and values. Understand our technical stack, which includes dbt, Fivetran, Prefect, Redshift, Postgres, AWS, and duckdb. Practice common data engineering interview questions on Interview Query to hone your skills and demonstrate your problem-solving abilities during the interview process.

The opportunity to join Resilience Lab as a Senior Data Engineer promises a dynamic role within a forward-thinking company revolutionizing mental health care. With a mission to enhance access and quality through state-of-the-art technology and a collaborative clinician community, Resilience Lab offers an ideal environment for growth and innovation. If you’re skilled in SQL, Python, and cloud data pipelines, and passionate about impactful solutions, this remote role backed by competitive compensation and robust benefits is your next career move. For more insights into the company and to prepare effectively, check out our main Resilience Lab Interview Guide on Interview Query, where we've covered many potential interview questions and detailed guides for different roles. Good luck with your interview!