Moveworks.Ai Data Engineer Interview Questions + Guide in 2025

Moveworks.Ai is dedicated to transforming how businesses operate through advanced AI-driven solutions that streamline operations and enhance productivity.

The Data Engineer role at Moveworks.Ai is pivotal in building and maintaining the data infrastructure that supports the company's analytics and machine learning capabilities. Key responsibilities include designing and implementing data pipelines, ensuring data integrity, and optimizing data storage solutions. A successful candidate will have a strong command of SQL, particularly in writing complex queries involving joins, window functions, and aggregations. Proficiency in algorithms and data modeling is crucial, along with experience in project scoping and stakeholder management. Strong communication skills and the ability to articulate technical concepts to non-technical stakeholders are essential traits for this position, as collaboration with various teams is a significant part of the role.

Preparing for an interview for this Data Engineer position at Moveworks.Ai will equip you with the knowledge and skills to demonstrate your technical expertise, problem-solving abilities, and cultural fit within the company.

The interview process for a Data Engineer at Moveworks.Ai is thorough and designed to assess both technical and interpersonal skills. It typically consists of multiple rounds, focusing on various aspects of the role.

1. Initial Screening

The process begins with an initial screening call, usually conducted by a recruiter or the hiring manager. This 30-45 minute conversation serves as an opportunity for both parties to get acquainted. The interviewer will discuss your background, work experience, and motivations for applying, while also providing insights into the company culture and the specifics of the Data Engineer role.

2. Stakeholder Management Round

Following the initial screening, candidates will participate in a stakeholder management round. This interview is typically led by a senior member of the marketing operations team. The focus here is on assessing your problem-solving abilities, communication skills, and overall fit for the role. Expect to discuss scenarios that demonstrate your capacity to manage stakeholder expectations and collaborate effectively.

3. Technical Assessment

The technical assessment is a critical component of the interview process. This round is usually conducted by a senior analytics engineer and emphasizes your proficiency in SQL. Candidates should be prepared to write queries based on given problem statements, showcasing their skills in aggregations, case statements, window functions, and joins. This round is essential for evaluating your technical capabilities and understanding of data manipulation.

4. Project Scoping and Team Fit

After the initial three rounds, candidates may face additional interviews focused on project scoping and team fit. These rounds are designed to evaluate how well you can define project requirements and your compatibility with the team dynamics. You may meet with the Head of GTM Operations and the Head of Demand Generation, who will assess your approach to project management and your ability to articulate your thoughts clearly.

5. Final Interview

The final interview typically involves a discussion with the hiring manager. This round aims to gauge your overall fit for the role and your genuine interest in the position. Expect to discuss your career aspirations, how you can contribute to the team, and any questions you may have about the role or the company.

Throughout the interview process, candidates are encouraged to engage actively, ask relevant questions, and demonstrate their knowledge about Moveworks.Ai and the Data Engineer role.

As you prepare for your interviews, it’s essential to be ready for the specific questions that may arise in each of these rounds.

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

Understand the Interview Structure

Moveworks.Ai typically conducts a multi-round interview process, often comprising six to seven rounds. Familiarize yourself with the structure, which usually includes an initial call with a hiring manager, followed by rounds focused on stakeholder management, technical skills, and team fit. Knowing what to expect will help you prepare effectively and reduce anxiety.

Showcase Your Technical Proficiency

As a Data Engineer, your technical skills will be under scrutiny, particularly in SQL. Be prepared to write queries that involve aggregations, case statements, window functions, and joins. Practice these concepts thoroughly, as they are crucial for demonstrating your ability to handle data effectively. Additionally, be ready to discuss your experience with schema design and pipeline building, as these are essential components of the role.

Emphasize Communication Skills

Communication is key at Moveworks.Ai, especially since the role involves collaboration with various stakeholders. During your interviews, focus on articulating your thoughts clearly and concisely. Practice explaining complex technical concepts in simple terms, as this will showcase your ability to bridge the gap between technical and non-technical teams. Be prepared to discuss how you’ve effectively communicated in past projects or situations.

Prepare for Problem-Solving Scenarios

Expect to encounter questions that assess your problem-solving skills and project scoping abilities. Be ready to discuss specific examples from your past work where you identified a problem, proposed a solution, and executed it successfully. This will demonstrate your analytical thinking and your fit for the role.

Research the Company Culture

Moveworks.Ai values team fit and culture fit highly. Take the time to understand the company’s mission, values, and recent developments. This knowledge will not only help you tailor your responses but also allow you to ask insightful questions during your interviews. Showing genuine interest in the company and its culture can set you apart from other candidates.

Ask Relevant Questions

During each interview round, come prepared with thoughtful questions that reflect your research and interest in the role. This not only demonstrates your enthusiasm but also gives you a chance to assess if the company aligns with your career goals. Questions about team dynamics, project expectations, and growth opportunities can provide valuable insights.

Reflect on Feedback

If you receive feedback during the interview process, take it seriously. Candidates have noted that articulating problems and solutions effectively is crucial. Use any feedback as a learning opportunity to improve your communication and presentation skills for future interviews.

By following these tips and preparing thoroughly, you can position yourself as a strong candidate for the Data Engineer role at Moveworks.Ai. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Moveworks.Ai. The interview process will assess your technical skills, problem-solving abilities, and fit within the company culture. Be prepared to demonstrate your expertise in SQL, algorithms, and your understanding of data engineering principles.

Technical Skills

1. Can you explain the difference between INNER JOIN and LEFT JOIN in SQL?

Understanding SQL joins is crucial for a Data Engineer role, as they are fundamental in data retrieval.

How to Answer

Clearly define both types of joins and provide examples of when to use each. Highlight the importance of understanding data relationships.

Example

“An INNER JOIN returns only the rows where there is a match in both tables, while a LEFT JOIN returns all rows from the left table and the matched rows from the right table. For instance, if I have a table of customers and a table of orders, an INNER JOIN would show only customers who have placed orders, whereas a LEFT JOIN would show all customers, including those who haven’t placed any orders.”

2. Describe a complex SQL query you wrote and the problem it solved.

This question assesses your practical experience with SQL and your problem-solving skills.

How to Answer

Discuss the context of the problem, the complexity of the query, and the outcome. Be specific about the SQL functions you used.

Example

“I once wrote a complex SQL query to analyze customer purchase patterns over a year. The query involved multiple JOINs, aggregations, and window functions to calculate the average purchase value per customer segment. This analysis helped the marketing team tailor their campaigns effectively, resulting in a 20% increase in engagement.”

3. How do you approach schema design for a new database?

Schema design is a critical aspect of data engineering, and your approach can reveal your understanding of data architecture.

How to Answer

Explain your methodology for designing a schema, including considerations for normalization, data types, and future scalability.

Example

“When designing a new database schema, I start by understanding the business requirements and the types of queries that will be run. I focus on normalization to reduce redundancy while ensuring that the schema can accommodate future growth. I also consider indexing strategies to optimize query performance.”

4. What are window functions in SQL, and when would you use them?

Window functions are essential for performing calculations across a set of table rows related to the current row.

How to Answer

Define window functions and provide scenarios where they are beneficial, emphasizing their role in analytics.

Example

“Window functions allow you to perform calculations across a set of rows that are related to the current row. I often use them for running totals or moving averages, which are crucial for time-series analysis. For example, calculating a moving average of sales over the last three months helps in understanding trends without losing granularity.”

Problem Solving and Project Management

5. Describe a time when you had to scope a data project. What steps did you take?

This question evaluates your project management skills and your ability to define project requirements.

How to Answer

Outline the steps you took to define the project scope, including stakeholder engagement and requirement gathering.

Example

“In a recent project, I was tasked with developing a data pipeline for a new product launch. I started by meeting with stakeholders to gather requirements and understand their goals. I then created a project plan that included timelines, resource allocation, and key milestones, ensuring that everyone was aligned before we began development.”

6. How do you ensure data quality in your projects?

Data quality is paramount in data engineering, and your approach can demonstrate your attention to detail.

How to Answer

Discuss the methods you use to validate and maintain data quality throughout the data lifecycle.

Example

“I ensure data quality by implementing validation checks at various stages of the data pipeline. This includes data profiling to identify anomalies, automated tests to catch errors early, and regular audits to maintain data integrity. Additionally, I encourage a culture of data stewardship within the team to promote accountability.”

7. Can you give an example of a challenging data problem you faced and how you solved it?

This question assesses your analytical thinking and problem-solving capabilities.

How to Answer

Describe the problem, your analysis process, and the solution you implemented, focusing on the impact of your work.

Example

“I faced a challenge when a data source was providing inconsistent data formats, which disrupted our reporting. I conducted a root cause analysis and discovered that the issue stemmed from a third-party API. I implemented a data transformation layer that standardized the incoming data formats, which resolved the issue and improved the reliability of our reports.”

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

This question evaluates your time management and prioritization skills.

How to Answer

Explain your approach to prioritizing tasks based on project deadlines, stakeholder needs, and resource availability.

Example

“I prioritize tasks by assessing project deadlines and the impact of each task on overall project success. I use project management tools to track progress and communicate with stakeholders regularly to ensure alignment. This approach allows me to focus on high-impact tasks while remaining flexible to adjust priorities as needed.”