Highmark Health Data Engineer Interview Questions + Guide in 2025

Highmark Health is committed to delivering remarkable health experiences and free individuals to be their best by leveraging advanced data solutions.

As a Data Engineer at Highmark Health, your primary responsibility is to design, build, and maintain data solutions that enhance operational and analytic capabilities across various platforms, including traditional data warehouses and cloud environments. You will collaborate with cross-functional teams to create high-performance data systems that support a Person-360 ecosystem, aligning data sourcing and flow with business needs. Key responsibilities include coding data ingestion pipelines, ensuring data quality, and managing data governance practices. Your experience should ideally encompass cloud technologies, big data solutions, and strong SQL skills, with a keen understanding of healthcare data challenges. The ability to communicate effectively with both technical and non-technical stakeholders is crucial, as you will be tasked with leading and mentoring team members while driving data transformation initiatives.

This guide will help you prepare for your interview by providing insights into the essential skills and experiences that Highmark Health values in a Data Engineer, positioning you to articulate your strengths and showcase your fit for the role confidently.

The interview process for a Data Engineer position at Highmark Health is structured to assess both technical and interpersonal skills, ensuring candidates are well-suited for the collaborative and innovative environment of the organization. The process typically includes several stages, each designed to evaluate different aspects of a candidate's qualifications and fit for the role.

1. Application and Initial Screening

After submitting your application, you will receive an email confirming the status of your application. If selected, you will be invited to complete a talent assessment, which may include questions related to your technical skills and problem-solving abilities. Following this, a recruiter will schedule a phone interview to discuss your background, motivations, and fit for the company culture.

2. Technical Interview

The technical interview is often conducted via video call and focuses on your proficiency in data engineering concepts, tools, and technologies. Expect to discuss your experience with SQL, data warehousing, and cloud platforms, as well as your familiarity with big data technologies. You may also be asked to solve problems or provide examples of past projects that demonstrate your technical capabilities.

3. Behavioral Interview

In this stage, you will engage in a behavioral interview with one or more team members, including managers or senior engineers. This interview will explore your past experiences, teamwork, and how you handle challenges in a work environment. Questions may revolve around your approach to project deadlines, collaboration with cross-functional teams, and how you manage stakeholder relationships.

4. Onsite Interview

The onsite interview typically consists of multiple rounds with various team members, including technical and managerial staff. You will be assessed on your technical skills through practical exercises or case studies, as well as your ability to communicate complex ideas effectively. This is also an opportunity for you to meet potential colleagues and get a feel for the team dynamics.

5. Final Interview and Offer

If you successfully navigate the previous stages, you may be invited for a final interview with higher-level management or executives. This conversation will likely focus on your long-term career goals, alignment with the company's mission, and how you can contribute to the organization. If all goes well, you will receive an offer, which will be followed by background checks and other pre-employment requirements.

As you prepare for your interview, consider the types of questions that may arise in each of these stages, particularly those that relate to your technical expertise and past experiences.

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Highmark Health. The interview process will likely focus on your technical skills, problem-solving abilities, and experience in data engineering, particularly in healthcare or similar regulated industries. Be prepared to discuss your past projects, technical knowledge, and how you approach challenges in data management and engineering.

Technical Skills

1. What is your experience with SQL and how have you used it in your previous roles?

This question assesses your proficiency in SQL, which is crucial for data manipulation and querying.

How to Answer

Discuss specific projects where you utilized SQL for data extraction, transformation, or analysis. Highlight any complex queries you wrote and the impact they had on your work.

Example

“In my last role, I used SQL extensively to extract data from our data warehouse for reporting purposes. I wrote complex queries involving multiple joins and subqueries to generate insights that helped the marketing team optimize their campaigns, resulting in a 20% increase in engagement.”

2. Can you explain the concept of data warehousing and its importance?

This question tests your understanding of data warehousing principles and their application in business intelligence.

How to Answer

Define data warehousing and explain its role in consolidating data from different sources for analysis. Mention its importance in decision-making processes.

Example

“Data warehousing is the process of collecting and managing data from various sources to provide meaningful business insights. It allows organizations to analyze historical data, which is crucial for strategic decision-making and forecasting.”

3. Describe your experience with cloud data platforms, particularly GCP or AWS.

This question evaluates your familiarity with cloud technologies, which are essential for modern data engineering.

How to Answer

Share specific experiences where you utilized cloud platforms for data storage, processing, or analytics. Mention any tools or services you used.

Example

“I have worked with Google Cloud Platform for building data pipelines using BigQuery and Dataflow. I designed a data ingestion process that automated the flow of data from our operational databases to BigQuery, significantly reducing the time needed for reporting.”

4. What is your approach to data cleansing and standardization?

This question assesses your understanding of data quality and the processes you implement to ensure clean data.

How to Answer

Discuss the techniques you use for data cleansing, such as removing duplicates, handling missing values, and standardizing formats.

Example

“I typically start with exploratory data analysis to identify inconsistencies and missing values. I then use Python scripts to automate the cleansing process, ensuring that all data adheres to a standard format before it’s loaded into our data warehouse.”

5. How do you ensure data security and compliance in your projects?

This question focuses on your awareness of data governance and security practices, especially in a healthcare context.

How to Answer

Explain the measures you take to protect sensitive data and comply with regulations like HIPAA.

Example

“I prioritize data security by implementing encryption for sensitive data both at rest and in transit. I also ensure that access controls are in place, and I regularly audit our data processes to comply with HIPAA regulations.”

Problem-Solving and Experience

1. Describe a challenging data engineering problem you faced and how you resolved it.

This question evaluates your problem-solving skills and ability to handle complex situations.

How to Answer

Provide a specific example of a challenge, the steps you took to address it, and the outcome.

Example

“Once, I encountered performance issues with a data pipeline that was causing delays in reporting. I analyzed the bottlenecks and optimized the SQL queries, which improved the processing time by 50%, allowing timely access to critical data.”

2. How do you prioritize tasks when working on multiple projects?

This question assesses your time management and organizational skills.

How to Answer

Discuss your approach to prioritization, such as using project management tools or methodologies.

Example

“I use a combination of Agile methodologies and project management tools like Jira to prioritize tasks based on deadlines and project impact. This helps me stay organized and ensures that I meet critical deadlines without compromising quality.”

3. Can you give an example of how you collaborated with cross-functional teams?

This question evaluates your teamwork and communication skills.

How to Answer

Share an experience where you worked with different teams, highlighting your role and contributions.

Example

“I collaborated with data scientists and business analysts to develop a predictive analytics model. I provided the necessary data infrastructure and ensured that the data was clean and accessible, which facilitated the model’s development and improved its accuracy.”

4. What tools and technologies do you prefer for data pipeline development?

This question assesses your technical preferences and familiarity with industry-standard tools.

How to Answer

Mention the tools you have experience with and why you prefer them.

Example

“I prefer using Apache Airflow for orchestrating data pipelines due to its flexibility and ease of use. For data processing, I often use Apache Spark because of its speed and ability to handle large datasets efficiently.”

5. How do you stay updated with the latest trends in data engineering?

This question evaluates your commitment to continuous learning and professional development.

How to Answer

Discuss the resources you use to keep your skills current, such as online courses, webinars, or industry publications.

Example

“I regularly follow industry blogs, participate in webinars, and take online courses on platforms like Coursera and Udacity. I also attend local meetups to network with other professionals and share knowledge about emerging technologies.”