The International Rescue Committee (IRC) is a renowned organization dedicated to responding to some of the world's most severe humanitarian crises. Established in 1933 at the urging of Albert Einstein, the IRC has grown to offer lifesaving aid and life-changing support to millions of displaced and struggling people across over 40 countries and 28 U.S. cities.

As a Data Engineer at IRC, you will play a pivotal role in the CRM Audience Management Team within the Global Marketing Technology division. This position is fully remote and open to candidates in the US, UK, and Colombia. The primary focus will be maintaining IRC's audience management architecture using SQL Server and Salesforce, supporting various marketing channels to bolster fundraising initiatives. This guide, hosted by Interview Query, will help you navigate the interview process, understand key responsibilities, and prepare effectively for the role. Dive in to gain valuable insights and tips!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining the International Rescue Committee (IRC) as a Data Engineer. Whether you were contacted by an IRC 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 IRC 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 IRC 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 IRC 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 IRC’s data systems, ETL pipelines, and SQL queries.

In the case of data engineering roles, take-home assignments and coding challenges related to data processing, SQL optimization, and ETL frameworks are incorporated. Apart from these, your proficiency in handling relational databases, data quality routines, and experience with CRM systems like Salesforce 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 IRC office or virtually if remote. Your technical prowess, including SQL programming, data management, and database development 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 IRC.

Quick Tips For IRC Data Engineer Interviews

• Be Prepared for SQL Challenges: The IRC Data Engineer role involves significant interaction with SQL databases. Brush up on your SQL skills, including complex queries, performance tuning, and ETL processes.
• Understand IRC’s Mission: IRC operates in the humanitarian sector, and being knowledgeable about their mission, values, and global impact can make a significant difference. Express how your skills can contribute to their goals.
• Showcase Versatility and Flexibility: The IRC values the ability to handle a variety of tasks and manage high work volumes. Highlight experiences where you've successfully managed multiple projects and adjusted priorities.

Typically, interviews at International Rescue Committee vary by role and team, but commonly Data Engineer interviews follow a fairly standardized process across these question topics.

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test multiple changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• Why has the number of job applicants been decreasing despite stable job postings? You observe that the number of job postings per day has remained constant over the last few months, but the number of applicants has been steadily decreasing. What could be the reasons for this trend?

• Can unbalanced sample sizes in an A/B test result in bias towards the smaller group? You need to analyze an A/B test where one variant has a sample size of 50K users and the other has 200K users. Can the unbalanced sizes lead to bias towards the smaller group?

• How can you verify if assignment to A/B test buckets was truly random? In an A/B test, how would you check if the assignment to various buckets was genuinely random?

• How would you assess the validity of an A/B test result with a 0.04 p-value? Your company is running a standard control and variant A/B test to increase conversion rates on a landing page. The PM finds a p-value of 0.04 in the results. How would you evaluate the validity of this result?

• What are the key differences between classification models and regression models? Explain the primary distinctions between classification and regression models, focusing on their objectives, output types, and typical use cases.

• What happens when you run logistic regression on perfectly linearly separable data? Describe the behavior and potential issues of logistic regression when applied to a dataset that is perfectly linearly separable.

• When would you use a bagging algorithm versus a boosting algorithm? Compare the scenarios in which bagging and boosting algorithms are preferable, and provide examples of the tradeoffs between the two.

• What’s the difference between Lasso and Ridge Regression? Clarify the differences between Lasso and Ridge Regression, focusing on their regularization techniques and effects on model coefficients.

• How does random forest generate the forest, and why use it over logistic regression? Explain the process of generating a random forest and discuss the advantages of using random forest over logistic regression in certain scenarios.

• What are time series models and why are they needed over simpler regression models? Explain what time series models are and discuss why they are necessary when simpler regression models might not suffice.

• What happens when you run logistic regression on perfectly linearly separable data? Given a dataset that is perfectly linearly separable, describe the outcome of running logistic regression on it.

• What is the probability of rolling at least one 3 with 2 dice? You are playing a dice game with 2 dice. Calculate the probability of rolling at least one 3. Extend this to (N) dice.

• Can an AB test with unbalanced sample sizes result in bias towards the smaller group? Analyze the potential bias in an AB test where one variant has 50K users and the other has 200K users due to the unbalanced sample sizes.

• What happens to the target metric after applying a new UI that won by 5% in an AB test? If a new UI tested on a random subset of users wins by 5% on the target metric, predict the change in the metric when the new UI is applied to all users, assuming no novelty effect.

What is the average salary for a Data Engineer at International Rescue Committee?

Q: What is the International Rescue Committee (IRC)?

A: The International Rescue Committee (IRC) is a global humanitarian organization founded in 1933 at the request of Albert Einstein. It responds to the world's worst crises, helping people to survive and rebuild their lives. The IRC operates in over 40 countries and 28 U.S. cities, providing lifesaving care and life-changing assistance.

Q: What does the Data Engineer role at IRC entail?

A: As a Data Engineer at IRC, you'll be leading the CRM Audience Management Team within the Global Marketing Technology Team. You’ll focus on maintaining the audience management architecture, managing SQL Server and Salesforce environments, and supporting direct mail audience needs across the US, UK, and global markets. The role includes tasks such as creating queries, data quality routines, delivering process improvements, and providing ongoing support and training.

Q: What are the key qualifications for the Data Engineer position?

A: The position requires a minimum of 8 years of experience with relational database technologies, especially MSSQL, SQL Server tools (T-SQL, SSIS, SSRS), and CRM databases. You should have strong analytical and problem-solving skills, proficiency in programming languages such as Excel VBA/macros and MSSQL queries, and experience in data quality checks, ETL design, and data warehouse solutions. Non-profit experience and familiarity with Salesforce are a plus.

Q: What is the working environment like for this role?

A: The Data Engineer role is fully remote, available to candidates in the US, UK, and Colombia. You will work closely with global colleagues and external vendors, handling tasks that support IRC’s fundraising and audience data management operations.

Q: How can I prepare for an interview for the Data Engineer position at IRC?

A: To prepare, you should review your technical skills related to SQL, CRM databases, and data management. Familiarize yourself with IRC’s mission and the specific requirements of the job. Practice answering common technical and behavioral interview questions using resources like Interview Query.

The Data Engineer position at the International Rescue Committee (IRC) offers a unique opportunity to work with a global leader in humanitarian relief. As part of the IRC’s Global Marketing Technology team, you will significantly impact audience data management and drive fundraising goals. The role demands technical proficiency with SQL and Salesforce, along with excellent problem-solving and communication skills. If you are passionate about data engineering and want to contribute to a cause that makes a difference worldwide, this is the right opportunity for you.

If you want more insights about the company, check out our main International Rescue Committee Interview Guide, where we have covered many interview questions that could be asked. At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every International Rescue Committee Data Engineer interview question and challenge.

Good luck with your interview!