Eleanor Health is a pioneering outpatient addiction and mental health provider dedicated to delivering compassionate, comprehensive care through a value-based payment structure. With a mission to transform the quality, delivery, and accessibility of care for those impacted by addiction, Eleanor Health operates multiple clinics and a fully virtual model across various states.

The Senior Data Engineer role is integral to Eleanor Health's mission. This position involves designing, building, and maintaining a highly reliable data and software platform that supports clinical teams and enhances member experience. The role demands expertise in cloud platforms and data technologies, along with a commitment to security, data integrity, and best practices in data engineering. As a Senior Data Engineer, you will mentor others, drive infrastructure improvements, and work collaboratively to achieve high-impact results.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Eleanor Health as a Data Engineer. Whether you were contacted by an Eleanor Health 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 experience.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Eleanor Health 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 Eleanor Health data engineering hiring manager stays 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 Eleanor Health data engineer role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Eleanor Health’s data systems, ETL pipelines, and SQL queries.

In the case of data engineering roles, take-home assignments regarding data processing, pipeline engineering, and data visualization might be incorporated. Apart from these, your proficiency in data modeling, schema design, and cloud platforms 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 Eleanor Health. Your technical prowess, including programming and database management 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 data engineer role at Eleanor Health.

Quick Tips For Eleanor Health Data Engineer Interviews

• Should contain three tips for interviewing for this specific company based on interview experiences.

Example:

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Eleanor Health interview include:

• Understand the Domain: Know the key aspects of addiction medicine and how data can transform it. Emphasize your knowledge about healthcare datasets and regulations like HIPAA.
• Be Technically Prepared: Review your knowledge of data processing frameworks (e.g., Spark), orchestration tools (e.g., Airflow), cloud platforms (e.g., Google Cloud), and coding languages (e.g., Python).
• Show Empathy and Passion: Eleanor Health values kindness, empathy, and product-mindedness. Demonstrate your passion for their mission and how your technical skills can make an impact.

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

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• How would you design a machine learning model to classify major health issues based on health features? You work as a machine learning engineer for a health insurance company. Design a model that classifies if an individual will undergo major health issues based on a set of health features.

• What metrics and statistical methods would you use to identify dishonest users in a sports tracking app? You work for a company with a sports app that tracks running, jogging, and cycling data. Formulate a method to identify users who might be cheating, such as driving a car while claiming to be on a bike ride. Specify the metrics and statistical methods you would analyze.

• Develop a function str_map to determine if a one-to-one correspondence exists between characters of two strings at the same positions. Given two strings, string1, and string2, write a function str_map to determine if there exists a one-to-one correspondence (bijection) between the characters of string1 and string2.

• Build a logistic regression model from scratch using gradient descent without an intercept term. Create a logistic regression model from scratch using basic gradient descent and the log-likelihood as the loss function. Do not include an intercept term or a penalty term. You may use numpy and pandas but not scikit-learn. Return the parameters of the regression.

• Why are job applications decreasing despite stable job postings? You are analyzing a job board where the number of job postings per day has remained stable, but the number of applicants has been steadily decreasing. What could be the reasons for this trend?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook informs you that friend requests have decreased by 10%. How would you approach this issue?

• How would you assess the validity of an AB test result with a .04 p-value? Your company is running an AB test on a feature to increase conversion rates on the landing page. The PM reports a p-value of .04. How would you evaluate the validity of this result?

• How would you analyze the performance of a new LinkedIn feature without an AB test? LinkedIn has launched a feature allowing candidates to message hiring managers directly during the interview process, but due to engineering constraints, an AB test was not conducted. How would you analyze the feature's performance?

• Should Square hire a customer success manager or offer a free trial for a new product? You are in charge of Square's small business division. The CEO wants to hire a customer success manager for a new software product, while another executive suggests offering a free trial instead. What would be your recommendation?

• How would you build a fraud detection model using a dataset of 600,000 credit card transactions? Imagine you work at a major credit card company and are given a dataset of 600,000 credit card transactions. Describe your approach to building a fraud detection model.

• How would you interpret coefficients of logistic regression for categorical and boolean variables? Explain how to interpret the coefficients of logistic regression when dealing with categorical and boolean variables.

• How would you tackle multicollinearity in multiple linear regression? Describe the methods you would use to address multicollinearity in a multiple linear regression model.

• How would you design a facial recognition system for employee clock-in and secure access? You work as an ML engineer for a large company that wants to implement a facial recognition system for employee clock-in, clock-out, and access to secure systems, including temporary contract consultants. How would you design this system?

• How would you handle data preparation for building a machine learning model using imbalanced data? Describe the steps you would take to prepare data for building a machine learning model when dealing with imbalanced data.

What is the average salary for a Data Engineer at Eleanor Health?

Q: What is the mission of Eleanor Health?

Eleanor Health is committed to transforming the quality, delivery, and accessibility of care for people affected by addiction and mental health challenges. We deliver comprehensive, whole-person care through a value-based payment structure, focusing on health and wellbeing without judgment.

Q: What are the key responsibilities for a Senior Data Engineer at Eleanor Health?

As a Senior Data Engineer, you will design and build a highly reliable data and software platform, promote best practices, and mentor other engineers. Key tasks include building and maintaining the cloud-native data platform and data processing pipelines, collaborating with cross-functional teams, and ensuring the infrastructure’s scalability, reliability, and security.

Q: What technologies does Eleanor Health use?

We employ Google Cloud Platform, GKE, Cloud SQL, Compute Engine, Datadog, and Terraform. Our data platform leverages BigQuery, Argo, Python, dbt, and more, while our software is primarily built using Go and TypeScript.

Q: What makes Eleanor Health's work environment unique?

Eleanor Health offers a remote work environment with flexible PTO, wellness days, and a supportive culture rooted in kindness, empathy, and product-mindedness. We emphasize personal accountability, empathy, and continuous improvement, ensuring that you can thrive both professionally and personally.

Q: How can I prepare for an interview at Eleanor Health?

To prepare, research Eleanor Health's mission and values, practice common interview questions with Interview Query, and review your technical skills, especially in cloud platforms like AWS or GCP. Being able to articulate your experiences in data engineering and your systematic approach to problem-solving will also be beneficial.

If you're excited to be part of a mission-driven team that promotes health and well-being through advanced technology and compassionate care, Eleanor Health offers a fantastic opportunity. To gear up for your interview, check out our main Eleanor Health Interview Guide, where we've compiled relevant interview questions and insights. Additionally, explore our guides for other roles such as software engineer and data analyst to understand Eleanor Health's comprehensive hiring process.

At Interview Query, we provide you with the resources, confidence, and strategic approach to excel in your Eleanor Health data engineer interview. Visit all our company interview guides for thorough preparation, and reach out if you have any questions.

Good luck with your interview!