Research Foundation Of The City University Of New York Software Engineer Interview Guide

Getting ready for a Software Engineer interview at Research Foundation Of The City University Of New York (RF CUNY)? The RF CUNY Software Engineer interview process typically spans 3–5 question topics and evaluates skills in areas like system design, SQL, software development, and technical communication. Interview prep is especially important for this role at RF CUNY, as engineers are expected to work on diverse projects supporting educational and research initiatives, often collaborating with stakeholders across academic and administrative environments. Candidates should be ready to discuss real-world technical challenges, their experience with learning management systems, and their ability to communicate complex solutions to non-technical audiences.

In preparing for the interview, you should:

• Understand the core skills necessary for Software Engineer positions at RF CUNY.
• Gain insights into RF CUNY’s Software Engineer interview structure and process.
• Practice real RF CUNY Software Engineer interview questions to sharpen your performance.

At Interview Query, we regularly analyze interview experience data shared by candidates. This guide uses that data to provide an overview of the RF CUNY Software Engineer interview process, along with sample questions and preparation tips tailored to help you succeed.

The Research Foundation of The City University of New York (RFCUNY) is a nonprofit organization supporting the research and sponsored programs of CUNY’s 25 campuses. RFCUNY provides administrative, financial, and technological infrastructure for faculty and staff engaged in scientific, educational, and community-focused initiatives. As a Software Engineer, you will contribute to building and maintaining systems that streamline research operations, directly supporting RFCUNY’s mission to advance academic inquiry and innovation across the university network.

As a Software Engineer at the Research Foundation of The City University Of New York, you will design, develop, and maintain software applications that support academic research and administrative operations. This role involves collaborating with researchers, faculty, and technical teams to understand project requirements and implement effective technical solutions. You will be responsible for writing clean, efficient code, troubleshooting issues, and ensuring the integrity and security of research data. Additionally, you may contribute to the integration of new technologies and provide technical support to various university initiatives. Your work helps advance the foundation’s mission by enabling innovative research and streamlining institutional processes.

2.1 Stage 1: Application & Resume Review

The process typically begins with an online application, where your resume and background are reviewed by HR or program coordinators. Emphasis is placed on academic credentials, relevant coursework, and prior experience with software engineering, particularly in educational or research settings. Highlighting technical proficiency with SQL, JavaScript, and any experience developing learning management systems (LMS) or similar platforms will strengthen your candidacy. Prepare a clear, concise resume that demonstrates both your technical and collaborative skills.

2.2 Stage 2: Recruiter Screen

After resume review, candidates may receive an email or phone call from a recruiter or HR representative. This initial conversation is focused on your interest in the organization, your availability, and confirming basic qualifications such as student status, relevant major, and eligibility (e.g., passing a background or drug test). Be ready to articulate why you are interested in this role and how your academic and technical background aligns with the organization's mission. Preparation should include reviewing the job requirements and being able to explain your motivation for applying.

2.3 Stage 3: Technical/Case/Skills Round

The technical interview is often conducted via Zoom or in-person and may be a single, comprehensive session. Expect a blend of technical and practical questions, including resume walkthroughs, in-depth discussions of your projects (especially those involving responsiveness, LMS development, or SQL advanced queries), and scenario-based questions. You may also be given a practical task, such as using a specific tool (e.g., INFO pass) or demonstrating your coding skills in SQL or JavaScript. To prepare, review your portfolio, be ready to discuss your technical decisions and problem-solving approaches, and practice explaining your project contributions clearly.

2.4 Stage 4: Behavioral Interview

Behavioral questions are frequently integrated with technical interviews and may be asked by directors, project managers, or team leads. These questions assess your ability to collaborate, communicate, and adapt within a team-oriented environment. You may be asked to describe how you handled challenges, worked with cross-functional stakeholders, or ensured project responsiveness. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Preparation should involve reflecting on past experiences where you demonstrated initiative, teamwork, or overcame obstacles.

2.5 Stage 5: Final/Onsite Round

For some candidates, the process may conclude with an onsite interview, typically involving meetings with both technical and non-technical staff, such as directors, immediate supervisors, or project managers. This round may include a practical assessment, such as completing a short technical task or discussing your approach to a real-world problem related to the role. The focus is on cultural fit, technical competency, and your ability to communicate solutions effectively. Prepare by researching the organization's projects and practicing how to present your ideas clearly to both technical and non-technical audiences.

2.6 Stage 6: Offer & Negotiation

If successful, you will receive an offer, often communicated via email or phone. At this stage, you may discuss the terms of employment, start date, and any additional requirements. Be prepared to provide documentation verifying your student status or major, and clarify any logistical details such as work location or assignment preferences. Preparation should include reviewing standard offer components and considering your requirements or questions for the role.

2.7 Average Timeline

The typical interview process at the Research Foundation Of The City University Of New York for Software Engineer roles ranges from one to three weeks, depending on scheduling and the number of interview rounds. Some candidates may progress quickly through a single, comprehensive interview, while others may experience multiple rounds with different stakeholders. Fast-track candidates with highly relevant skills and availability may receive offers within a week, while the standard pace allows for more thorough review and coordination among interviewers.

Next, let’s dive into the specific types of interview questions you can expect throughout this process.

3.1 SQL & Data Modeling

Expect questions that assess your ability to design, query, and optimize relational databases, as well as your understanding of data warehousing and schema design. You’ll need to demonstrate proficiency in SQL, data normalization, and translating business requirements into scalable data models.

3.1.1 Write a query to select the top 3 departments with at least ten employees and rank them according to the percentage of their employees making over 100K in salary.
Break down the problem using GROUP BY and HAVING to filter departments, and use window functions or subqueries to calculate and rank percentages. Be explicit about handling ties and edge cases.

3.1.2 Write a query to get the largest salary of any employee by department
Use aggregation functions and GROUP BY to partition data by department. Discuss how you’d handle departments with missing or null salary data.

3.1.3 Write a query to compute the average data scientist salary given a mapped linear recency weighting on the data.
Explain how to apply recency weights via CASE statements or joins, and aggregate the results. Clarify assumptions about the weighting scheme and data freshness.

3.1.4 Write a query to select the 2nd highest salary in the engineering department
Demonstrate the use of window functions like ROWNUMBER or DENSERANK to retrieve the correct record. Mention how you’d handle duplicate salaries.

3.1.5 Write a query to determine which database tables an application uses for a specific record without access to its source code
Describe strategies such as analyzing query logs, using database triggers, or reverse engineering via metadata. Highlight your approach to systematically mapping dependencies.

3.2 System & Application Design

These questions test your ability to architect robust, scalable systems for real-world scenarios. Focus on how you break down requirements, choose technologies, and ensure maintainability and security.

3.2.1 Design a data warehouse for a new online retailer
Outline key fact and dimension tables, discuss ETL strategies, and justify schema choices (star vs. snowflake). Address scalability and data quality controls.

3.2.2 Design a database for a ride-sharing app.
Identify core entities (users, rides, payments), relationships, and indexing strategies. Discuss how to accommodate high transaction volumes and real-time queries.

3.2.3 System design for a digital classroom service.
Break the problem into user management, content delivery, and communication modules. Explain how you’d ensure data privacy and scale for concurrent users.

3.2.4 Design the system supporting an application for a parking system.
Describe the entities, workflows, and real-time requirements. Highlight how you’d handle peak loads and data consistency.

3.2.5 Design a secure and scalable messaging system for a financial institution.
Focus on security, encryption, and compliance, as well as high availability. Discuss your approach to auditing and user authentication.

3.3 Data Engineering & Processing

These questions evaluate your ability to handle large datasets, data cleaning, and ETL processes. Show your attention to data quality, efficiency, and reproducibility.

3.3.1 Describing a real-world data cleaning and organization project
Explain your step-by-step process for profiling, cleaning, and documenting changes. Emphasize tools, automation, and impact on downstream analysis.

3.3.2 Ensuring data quality within a complex ETL setup
Discuss monitoring, validation checks, and troubleshooting strategies. Highlight how you communicate data quality issues to stakeholders.

3.3.3 Write a function to return the names and ids for ids that we haven't scraped yet.
Describe your approach to deduplication and incremental data processing. Mention how you’d optimize performance for large-scale operations.

3.3.4 Write a query to find the total salary of slacking employees.
Show how you’d use filtering and aggregation to identify and sum relevant records. Clarify how you define and detect “slacking” in the dataset.

3.4 Communication & Presentation of Insights

Presentation and communication skills are critical for translating technical findings into actionable insights for diverse audiences. Expect questions about tailoring your message and ensuring clarity.

3.4.1 How to present complex data insights with clarity and adaptability tailored to a specific audience
Describe frameworks for structuring presentations, adapting visuals, and gauging audience understanding. Provide examples of simplifying technical jargon.

3.4.2 Demystifying data for non-technical users through visualization and clear communication
Explain how you select visualization types, annotate charts, and use analogies. Emphasize your approach to fostering data literacy.

3.4.3 Making data-driven insights actionable for those without technical expertise
Share methods for summarizing key takeaways and linking insights to business objectives. Highlight your experience with executive summaries or dashboards.

3.5 Behavioral Questions

3.5.1 Tell me about a time you used data to make a decision.
Describe a specific scenario, the data you analyzed, and the impact of your recommendation. Focus on how your analysis influenced a meaningful business outcome.

3.5.2 Describe a challenging data project and how you handled it.
Outline the project’s objectives, the obstacles you faced, and the concrete steps you took to overcome them. Emphasize problem-solving and adaptability.

3.5.3 How do you handle unclear requirements or ambiguity?
Share your process for clarifying goals, collaborating with stakeholders, and iteratively refining your approach. Highlight communication and flexibility.

3.5.4 Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?
Explain the communication gap, your strategies for bridging it, and the result. Focus on listening, empathy, and adjusting your message.

3.5.5 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Describe how you built credibility, presented evidence, and navigated organizational dynamics. Emphasize persuasion and relationship-building.

3.5.6 Give an example of automating recurrent data-quality checks so the same dirty-data crisis doesn’t happen again.
Walk through the tools or scripts you developed, how you implemented them, and the impact on workflow efficiency and data reliability.

3.5.7 How do you prioritize multiple deadlines? Additionally, how do you stay organized when you have multiple deadlines?
Share your prioritization framework, tools, and communication strategies. Provide an example of balancing competing demands successfully.

3.5.8 Tell me about a time you delivered critical insights even though 30% of the dataset had nulls. What analytical trade-offs did you make?
Discuss your approach to handling missing data, the methods you used, and how you communicated limitations. Highlight transparency and decision-making under uncertainty.

3.5.9 Tell me about a time when you exceeded expectations during a project. What did you do, and how did you accomplish it?
Describe the context, the actions you took to go above and beyond, and the measurable impact. Focus on initiative, ownership, and creativity.

4.1 Company-specific tips:

Familiarize yourself with the mission and operations of the Research Foundation Of The City University Of New York (RF CUNY). Understand how their software engineering teams support research, academic programs, and administrative functions across CUNY’s campuses. Dive into recent RF CUNY initiatives and technology projects, especially those that automate or streamline educational workflows, research data management, or grant administration. Be prepared to discuss how your technical skills and experience can directly contribute to advancing RF CUNY’s goals of academic excellence and innovation.

Research the types of stakeholders you’ll be collaborating with at RF CUNY, including faculty, researchers, and administrative staff. Practice explaining technical concepts in clear, accessible language, as you’ll often need to communicate with non-technical audiences. Review RF CUNY’s commitment to data privacy, security, and compliance, as these are critical in an academic research setting. Be ready to articulate your understanding of ethical software development within a nonprofit and educational context.

4.2 Role-specific tips:

4.2.1 Brush up on SQL and data modeling concepts relevant to academic and administrative systems.
Expect to solve SQL queries involving aggregation, ranking, and handling edge cases with missing or null data. Practice writing queries that analyze department-level metrics, employee salaries, and recency-weighted averages. Demonstrate your ability to design normalized schemas and optimize queries for large, complex datasets typical of university environments.

4.2.2 Prepare to discuss system and application design for diverse educational and research scenarios.
Be ready to architect solutions for digital classroom services, learning management systems, and administrative platforms. Break down requirements into core modules—such as user management, content delivery, and data privacy—and justify your technology choices. Show how you ensure scalability, maintainability, and security in your designs, especially when handling sensitive academic data.

4.2.3 Highlight your experience with data engineering and ETL processes.
Describe real-world projects where you cleaned, organized, and validated large datasets. Emphasize your attention to data quality, reproducibility, and automation of data-quality checks. Be prepared to explain how you handle deduplication, incremental processing, and performance optimization for university-scale operations.

4.2.4 Demonstrate strong technical communication and presentation skills.
Practice presenting complex data insights to both technical and non-technical stakeholders. Structure your explanations to be clear and actionable, using visualizations and analogies when appropriate. Share examples of tailoring your message to diverse audiences, such as faculty members or administrative staff, and how you foster understanding and data literacy.

4.2.5 Prepare behavioral stories that showcase collaboration, adaptability, and initiative.
Reflect on past experiences working in cross-functional teams or with ambiguous requirements. Use the STAR method to describe how you clarified goals, overcame challenges, and delivered impactful solutions. Highlight moments when you influenced stakeholders, automated processes, or exceeded expectations on a project.

4.2.6 Be ready to discuss your approach to balancing multiple priorities and deadlines.
Share specific strategies for organizing your work, communicating progress, and managing competing demands. Provide examples of how you’ve successfully juggled multiple projects in fast-paced or resource-constrained environments, demonstrating your reliability and commitment to quality.

4.2.7 Show your commitment to ethical, secure, and user-focused software development.
Articulate your understanding of data privacy, especially in educational and nonprofit settings. Discuss how you build secure systems and handle sensitive information responsibly. Demonstrate your awareness of accessibility and user experience best practices, ensuring that your solutions benefit all stakeholders across the university.

By preparing these targeted examples and sharpening your technical and communication skills, you’ll be well-positioned to excel in the RF CUNY Software Engineer interview and make a meaningful impact within their academic and research community.

5.1 How hard is the Research Foundation Of The City University Of New York Software Engineer interview?
The RF CUNY Software Engineer interview is challenging but approachable for candidates with a solid foundation in software development, SQL, and system design. The process emphasizes practical problem-solving, technical communication, and the ability to work on projects that support educational and research initiatives. Expect questions that assess both your coding skills and your ability to translate technical solutions for diverse stakeholders.

5.2 How many interview rounds does Research Foundation Of The City University Of New York have for Software Engineer?
Typically, the interview process consists of three to five stages: resume review, recruiter screen, technical/case interview, behavioral interview, and possibly a final onsite round. Some candidates may experience a condensed process with fewer rounds, especially if their skills closely match the job requirements.

5.3 Does Research Foundation Of The City University Of New York ask for take-home assignments for Software Engineer?
While take-home assignments are not always required, you may be given a practical task or technical assessment during the interview process. These can include coding exercises, data modeling problems, or scenario-based challenges relevant to academic and research systems.

5.4 What skills are required for the Research Foundation Of The City University Of New York Software Engineer?
Key skills include proficiency in SQL, software development (often with JavaScript or similar languages), system design, data modeling, and technical communication. Experience with learning management systems, data privacy, and collaborating with non-technical stakeholders is highly valued. Candidates should also demonstrate adaptability, teamwork, and a commitment to ethical software development.

5.5 How long does the Research Foundation Of The City University Of New York Software Engineer hiring process take?
The typical timeline ranges from one to three weeks, depending on the number of interview rounds and the availability of both candidates and interviewers. Fast-track candidates may receive an offer within a week, while others may progress at a more measured pace to allow for thorough evaluation and coordination.

5.6 What types of questions are asked in the Research Foundation Of The City University Of New York Software Engineer interview?
Expect a blend of technical questions (SQL queries, system design, data engineering), scenario-based challenges, and behavioral questions focused on collaboration, communication, and problem-solving. You may also be asked to discuss your experience with academic or research systems, and to explain technical concepts to non-technical audiences.

5.7 Does Research Foundation Of The City University Of New York give feedback after the Software Engineer interview?
RF CUNY typically provides high-level feedback through recruiters, especially for candidates who progress to later stages. Detailed technical feedback may be limited, but you can expect to hear about your overall fit and strengths.

5.8 What is the acceptance rate for Research Foundation Of The City University Of New York Software Engineer applicants?
While specific acceptance rates are not published, the role is competitive given the emphasis on technical skills and mission-driven experience. Candidates with relevant backgrounds in educational or research technology have a stronger chance of advancing.

5.9 Does Research Foundation Of The City University Of New York hire remote Software Engineer positions?
RF CUNY offers some flexibility for remote work, especially for software engineering roles supporting university-wide projects. However, certain positions may require occasional in-person meetings or collaboration with campus-based teams, so be sure to clarify expectations during the interview process.

• Related guides:
  • Research Foundation Of The City University Of New York interview questions
  • Software Engineer interview guide
  • “Top Software Engineering interview tips”

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