Moss Adams LLP Data Engineer Interview Questions + Guide in 2025

Moss Adams LLP is a leading professional services firm that emphasizes authenticity and a culture of care for its clients, employees, and communities.

The Data Engineer plays a critical role in the Data Platform Team, focusing on developing, testing, and maintaining the firm's analytical data assets to support various business intelligence applications, workflows, and reporting needs. Key responsibilities include designing scalable data processing pipelines, managing Azure Machine Learning environments, and developing ETL processes using tools like Data Factory and SQL Server Integration Services (SSIS). A strong foundation in SQL, particularly T-SQL, along with expertise in Python, Snowflake data cloud, and Azure data assets, is essential. Additionally, familiarity with Power BI for data visualization and a solid grasp of data integration, warehousing, and dimensional modeling are important for success in this role.

Moss Adams values collaboration, critical thinking, and emotional intelligence, which are crucial traits for thriving within the team. By preparing with this guide, you'll be equipped with the knowledge and confidence needed to excel in your interview and highlight your fit for the Data Engineer role at Moss Adams.

The interview process for a Data Engineer at Moss Adams is structured to assess both technical skills and cultural fit within the organization. It typically consists of several rounds, each designed to evaluate different aspects of the candidate's qualifications and experiences.

1. Initial Screening

The first step in the interview process is an initial screening, usually conducted by a recruiter. This is a brief conversation, often lasting around 15-30 minutes, where the recruiter will ask you to introduce yourself and discuss your background. They will review your resume and may ask a few preliminary questions to gauge your interest in the role and the company. This is also an opportunity for you to ask questions about the company culture and the specifics of the role.

2. Technical Interview

Following the initial screening, candidates typically undergo a technical interview. This round may involve one or more interviewers, including senior data engineers or technical leads. The focus here is on assessing your technical expertise, particularly in SQL, Python, and data warehousing concepts. You may be asked to solve coding problems, discuss your experience with ETL processes, and demonstrate your understanding of data integration and data quality issues. Be prepared to explain your thought process and approach to problem-solving.

3. Behavioral Interview

The next stage often includes a behavioral interview, which is designed to evaluate your soft skills and cultural fit within the team. This round may involve multiple interviewers, including managers and team leads. Expect questions that explore your past experiences, teamwork, and how you handle challenges. The interviewers will be looking for evidence of collaboration, critical thinking, and emotional intelligence, as these are key attributes valued at Moss Adams.

4. Final Interview

In some cases, there may be a final interview round that includes back-to-back sessions with senior leadership or partners. This round is typically more conversational and may focus on your long-term career goals, your understanding of the firm's mission, and how you can contribute to the team. You may also be asked to discuss specific projects you've worked on and how they relate to the responsibilities of the Data Engineer role.

Throughout the interview process, candidates are encouraged to ask questions to better understand the role and the company culture. This not only demonstrates your interest but also helps you assess if Moss Adams is the right fit for you.

Now that you have an overview of the interview process, let's delve into the specific questions that candidates have encountered during their interviews.

Here are some tips to help you excel in your interview.

Emphasize Your Technical Proficiency

Given the role's heavy reliance on SQL and Python, ensure you can demonstrate your expertise in these areas. Be prepared to discuss specific projects where you utilized SQL for data manipulation, ETL processes, or database management. Highlight your experience with Snowflake and Azure, as these are critical to the position. If you have worked with SQL Server 2019, be ready to explain your role in any migration projects and how you approached challenges during the process.

Showcase Your Problem-Solving Skills

Moss Adams values critical thinking and analytical skills. Prepare to discuss scenarios where you identified data quality issues or gaps in data integration. Use the STAR (Situation, Task, Action, Result) method to structure your responses, focusing on how your actions led to successful outcomes. This will not only demonstrate your problem-solving abilities but also your results-oriented mindset.

Prepare for Behavioral Questions

Expect a mix of technical and behavioral questions. The interviewers will likely assess your collaboration and emotional intelligence, so be ready to share experiences that highlight your ability to work effectively in teams. Reflect on times when you had to navigate tight deadlines or manage conflicting priorities, and how you maintained exceptional client service throughout.

Engage with Your Interviewers

The interview process at Moss Adams is described as friendly and conversational. Use this to your advantage by asking insightful questions about the team dynamics, ongoing projects, and the company culture. This not only shows your interest in the role but also allows you to gauge if the environment aligns with your values and work style.

Demonstrate Your Growth Mindset

Moss Adams appreciates candidates who exhibit a growth mindset and intellectual curiosity. Share examples of how you have pursued continuous learning, whether through formal education, certifications, or self-directed projects. Discuss how you stay updated with industry trends and technologies, particularly in data engineering and analytics.

Be Authentic and Personable

The company champions authenticity, so be yourself during the interview. Share your passion for data engineering and how it aligns with Moss Adams' mission of empowering others. Authenticity can help you connect with your interviewers on a personal level, making a lasting impression.

Follow Up Thoughtfully

After the interview, send a personalized thank-you note to express your appreciation for the opportunity to interview. Mention specific topics discussed during the interview to reinforce your interest in the role and the company. This small gesture can set you apart from other candidates and demonstrate your professionalism.

By focusing on these areas, you can present yourself as a well-rounded candidate who not only possesses the necessary technical skills but also aligns with the values and culture of Moss Adams. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Moss Adams LLP. The interview process will likely focus on your technical skills, problem-solving abilities, and your capacity to work collaboratively within a team. Be prepared to discuss your experience with SQL, data warehousing, ETL processes, and your understanding of data integration and analytics.

Technical Skills

1. Can you explain the ETL process and how you have implemented it in your previous projects?

Understanding the ETL (Extract, Transform, Load) process is crucial for a Data Engineer, as it is fundamental to data integration and warehousing.

How to Answer

Discuss your experience with ETL tools and frameworks, emphasizing specific projects where you successfully implemented ETL processes. Highlight any challenges you faced and how you overcame them.

Example

“In my previous role, I utilized SQL Server Integration Services (SSIS) to develop ETL processes for a large-scale data migration project. I extracted data from various sources, transformed it to meet business requirements, and loaded it into our data warehouse. One challenge was ensuring data quality during the transformation phase, which I addressed by implementing validation checks at each step.”

2. What is your experience with SQL and T-SQL? Can you provide an example of a complex query you wrote?

SQL proficiency is essential for a Data Engineer, especially in a role that involves data manipulation and reporting.

How to Answer

Share specific examples of complex SQL queries you have written, explaining the context and the outcome. Discuss any performance optimization techniques you used.

Example

“I have extensive experience with T-SQL, particularly in writing stored procedures and complex queries. For instance, I developed a query that aggregated sales data across multiple regions, which involved several joins and subqueries. This query not only improved our reporting efficiency but also provided insights that led to a 15% increase in sales in underperforming areas.”

3. How do you ensure data quality and integrity in your data pipelines?

Data quality is critical in data engineering, and interviewers will want to know your approach to maintaining it.

How to Answer

Discuss the methods and tools you use to monitor and validate data quality throughout the data pipeline. Mention any specific metrics or KPIs you track.

Example

“I implement data quality checks at various stages of the ETL process, including validation rules to catch anomalies during data ingestion. Additionally, I use automated testing frameworks to ensure that the data transformations yield accurate results. For instance, I set up alerts for any discrepancies in expected data volumes, which allows for quick remediation.”

Data Warehousing and Architecture

4. Can you describe your experience with data warehousing concepts and dimensional modeling?

A solid understanding of data warehousing is essential for a Data Engineer, especially in designing scalable architectures.

How to Answer

Explain your experience with data warehousing projects, focusing on dimensional modeling techniques like star and snowflake schemas.

Example

“I have worked on several data warehousing projects where I designed star schemas to optimize query performance. In one project, I created a data mart for sales analytics, which involved identifying key dimensions and facts. This structure allowed for efficient reporting and analysis, significantly reducing query times.”

5. What tools and technologies have you used for data integration and processing?

Familiarity with various tools is important for a Data Engineer, especially those relevant to the role.

How to Answer

List the tools you have experience with, such as Azure Data Factory, SSIS, or Snowflake, and provide examples of how you used them in your work.

Example

“I have utilized Azure Data Factory for orchestrating data workflows and integrating data from various sources. In a recent project, I set up data pipelines that pulled data from on-prem SQL Server databases and loaded it into Snowflake, ensuring seamless data flow and accessibility for analytics.”

Behavioral Questions

6. Describe a time when you had to work under tight deadlines. How did you manage your time?

Time management is crucial in a fast-paced environment, and interviewers will want to assess your ability to prioritize tasks.

How to Answer

Share a specific example that demonstrates your time management skills, focusing on how you organized your tasks and met the deadline.

Example

“During a critical project, I was tasked with delivering a data integration solution within a week. I prioritized my tasks by breaking down the project into manageable components and setting daily goals. By collaborating closely with my team and maintaining open communication, we successfully delivered the project on time, which was well-received by stakeholders.”

7. How do you handle conflicts within a team? Can you provide an example?

Collaboration is key in a team environment, and interviewers will want to know how you navigate conflicts.

How to Answer

Discuss your approach to conflict resolution, emphasizing communication and collaboration. Provide a specific example to illustrate your point.

Example

“In a previous project, there was a disagreement between team members regarding the data model design. I facilitated a meeting where everyone could voice their concerns and suggestions. By encouraging open dialogue, we were able to reach a consensus that incorporated the best ideas from each perspective, ultimately leading to a more robust solution.”