Barnabas Health is a prominent healthcare corporation dedicated to providing top-tier medical services and innovative health solutions. With a commitment to patient care and cutting-edge technology, the company stands out in the healthcare sector.

As a Data Engineer at Barnabas Health, you will play a crucial role in managing and analyzing complex healthcare data to support decision-making processes. This position demands profound technical expertise, robust understanding of data architecture, proficiency in coding, and experience with big data tools. A Data Engineer at Barnabas Health contributes to optimizing healthcare delivery by ensuring data integrity, implementing data pipelines, and facilitating seamless data flow across systems.

This guide on Interview Query will prepare you for the journey ahead, detailing the interview process, commonly asked questions, and indispensable tips to help you succeed. Prepare to embark on a career that blends technology and healthcare at Barnabas Health!

Submitting Your Application

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

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Barnabas 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 Barnabas Health Data Engineer 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 Barnabas 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 Barnabas Health’s data systems, ETL pipelines, and SQL queries.

In the case of Data Engineer roles, take-home assignments regarding data manipulation, processing techniques, and data architecture may be incorporated. Apart from these, your proficiency against cloud platforms, distributed systems, and data modeling fundamentals 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 Barnabas Health office. Your technical prowess, including programming and data engineering 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 Barnabas Health.

Quick Tips For Barnabas Health Data Engineer Interviews

• Understand the Healthcare Domain: Familiarize yourself with healthcare data systems and industry-specific data privacy standards such as HIPAA.
• Strong Programming Skills: Ensure you are proficient in data engineering languages such as Python, SQL, and Spark, as these are vital for the technical rounds.
• Showcase Problem-Solving Skills: Barnabas Health places strong emphasis on solving real-world data problems. Be prepared to discuss your problem-solving approach, especially in complex data environments.

Typically, interviews at Barnabas 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? As a machine learning engineer for a health insurance company, design a model that classifies whether 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 app? For a sports app tracking running, jogging, and cycling data, formulate a method to identify dishonest users, such as those driving a car while claiming to be on a bike ride. Specify the metrics and statistical methods you would analyze to detect athletic anomalies indicative of cheating.

• 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 and log-likelihood as the loss function. Create a logistic regression model from scratch without an intercept term. Use basic gradient descent (with Newton's method) for optimization and the log-likelihood as the loss function. Do not include 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 observe that the number of job postings per day has remained stable, but the number of applicants has been steadily decreasing. What could be causing 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 address this issue?

• How would you assess the validity of an AB test result with a 0.04 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 0.04. 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. Due to engineering constraints, an AB test wasn't possible. How would you analyze the feature's performance?

• Should Square hire a customer success manager or offer a free trial for a new product? Square's 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 to encourage new or existing customers to use the new product?

• 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. The system should also accommodate temporary contract consultants. How would you design this system?

• How would you handle data preparation for building a machine learning model using imbalanced data? Explain 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 Barnabas Health?

Q: What is the interview process at Barnabas Health for a Data Engineer position like?

A: The interview process at Barnabas Health typically involves an initial phone screen with a recruiter, followed by technical interviews that assess your data engineering skills. The final stage usually includes onsite interviews where you'll meet with team members and discuss your experience and technical knowledge.

Q: What skills are important for a Data Engineer at Barnabas Health?

A: Essential skills for a Data Engineer at Barnabas Health include proficiency in SQL, Python, and data warehousing. Experience with ETL processes, big data technologies like Hadoop or Spark, and cloud platforms such as AWS or Azure is also highly valued.

Q: What is the company culture like at Barnabas Health?

A: Barnabas Health promotes a collaborative and innovation-driven environment. The company values teamwork, continuous learning, and a commitment to improving healthcare outcomes. Employees are encouraged to bring forward new ideas and take initiative in solving complex problems.

Q: What are some benefits of working as a Data Engineer at Barnabas Health?

A: Barnabas Health offers competitive salaries, comprehensive healthcare benefits, and opportunities for professional development. Additionally, you’ll have the chance to work on impactful projects that contribute to improving patient care and overall healthcare services.

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

A: To prepare for an interview at Barnabas Health, it's essential to review your technical skills, especially in SQL, Python, and data warehousing. Practice common data engineering problems and algorithms. Familiarize yourself with healthcare data management if possible. Resources like Interview Query can provide useful practice questions and insights.

Embarking on a journey with Barnabas Health as a Data Engineer promises a rewarding and impactful experience. Whether you're fascinated by large-scale data management or driven by the desire to streamline healthcare analytics, Barnabas Health offers a dynamic and innovative environment. For deeper insights into the company's interview process and to boost your preparation, check out our main RWJBarnabas Health Interview Guide, where we've cataloged numerous interview questions specific to this role. Additionally, our interview guides for other positions, such as software engineer and data analyst, can provide broader insights into Barnabas Health’s recruitment approach.

At Interview Query, we aim to empower you with a comprehensive toolkit, ensuring you are well-prepared, confident, and strategically equipped to tackle every interview challenge at Barnabas Health. Explore all our company interview guides for enhanced preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!