Capco Overview

Capco, a Wipro company, is a global technology and management consulting firm renowned for its transformative projects in the financial services, banking, and energy sectors. With over 32 cities in its footprint, Capco serves more than 100 clients and has received accolades like the Consultancy of the Year at the British Bank Awards and inclusion in Avtar & Seramount's Top 100 Best Companies for Women in India 2022.

As a Data Engineer at Capco, you'll be responsible for designing and maintaining scalable data pipelines and developing new API integrations to manage increasing data volumes and complexity. You'll collaborate with analytics and business teams, enhancing data models to fuel business intelligence tools, and support data-driven decision-making across the organization.

Explore this guide on Interview Query to navigate Capco's interview process, key questions, and tips to succeed. Let’s get started!

Submitting Your Application

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

In the case of data engineering roles, take-home assignments regarding pipeline creation, debugging, and data processing are incorporated. Apart from these, your proficiency in big data tools like Hadoop, Spark, and Kafka 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 Capco office. Your technical prowess, including programming and data engineering 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 Capco.

Quick Tips For Capco Data Engineer Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. Here are a few tips for acing your Capco interview:

• Understand Big Data Tools: Capco's data engineering roles heavily focus on big data tools like Spark, Kafka, and Hadoop. Familiarize yourself with these tools and understand their core functionalities.
• Be Proficient in SQL and Scripting: Capco's data engineering interviews assess your proficiency in SQL and scripting languages like Python, Java, and Go. Brush up on your SQL querying and data manipulation skills.
• Demonstrate Problem-Solving Ability: Capco values innovative thinking and problem-solving. Practice responding to behavioral questions by highlighting instances where you successfully solved complex technical problems.

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

• Why is the average number of comments per user decreasing despite user growth? You work for a social media company that launched in a new city. From January to March, the average number of comments per user is decreasing, even though the number of new users is growing. What could be the reasons for this trend, and what metrics would you investigate?

• What would you do if friend requests are down 10%? A product manager at Facebook informs you that friend requests have decreased by 10%. What steps would you take to address this issue?

• How would you determine the value of each marketing channel for Mode? Mode, a company selling B2B analytics dashboards, provides you with data on different marketing channels and their respective costs. What metrics would you use to evaluate the value of each marketing channel?

• How would you find the mouse in a 4x4 grid using the fewest scans? You have a 4x4 grid with a mouse trapped in one of the cells. You can scan subsets of cells to determine if the mouse is within that subset. How would you locate the mouse using the minimum number of scans?

• What is flawed in the VP's approach to evaluating lead value and customer retention? You work for an insurance SAAS company that sells leads to agents. The VP of sales believes that more leads delivered to agents at month three (3x more than month one) proves higher value and longer customer retention. What could be potentially flawed in this approach?

• Create a query to count rows resulting from different joins between ads and the top 3 ads. Allstate is running N online ads ranked by popularity in the ads table. Create a subquery or common table expression named top_ads containing the top 3 ads by popularity. Return the number of rows resulting from INNER JOIN, LEFT JOIN, RIGHT JOIN, and CROSS JOIN operations between ads and top_ads. Include a join_type column in the output with values inner_join, left_join, etc. for each join type.

• How would you build a fraud detection model using a dataset of 600,000 credit card transactions? Imagine you work at a major credit card company and are given a dataset of 600,000 credit card transactions. Describe your approach to building a fraud detection model in the comments.

• When would you use a bagging algorithm versus a boosting algorithm? Let’s say we’re comparing two machine learning algorithms. Explain the scenarios in which you would use a bagging algorithm versus a boosting algorithm, and provide an example of the tradeoffs between the two.

• How would you generate respawn locations for an online third-person shooter game? Describe your approach to building a model or algorithm to generate respawn locations for an online third-person shooter game like Halo.

• What is the difference between XGBoost and random forest algorithms? Explain the difference between the XGBoost and random forest algorithms and provide an example where you would use one over the other.

• How would you explain what a p-value is to someone who is not technical? Explain the concept of a p-value in simple terms to someone without a technical background.

• Write a function to simulate coin tosses with a given probability of heads. Create a function that takes the number of tosses and the probability of heads as inputs and returns a list of 'H' and 'T' representing the outcomes.

• When would you use mean vs. median, and how do you calculate their confidence intervals? Given a dataset, explain when to use the mean versus the median and describe how to calculate the confidence interval for each measure.

• What is the probability that the second card picked has a different color or suit than the first? Calculate the probability that the second card drawn from a deck without replacement has a different color or suit than the first card.

• Can an unbalanced sample size in an AB test result in bias towards the smaller group? Analyze whether an AB test with one variant having 50K users and the other 200K users will be biased towards the smaller group due to the unbalanced sample sizes.

What is the average salary for a Data Engineer at Capco?

Q: What is the interview process like at Capco for the Data Engineer position?

A: The interview process at Capco typically involves multiple stages including an aptitude test, then a technical screening round, followed by one or more technical interviews. The entire process can take up to a month.

Q: What technical skills are required for the Data Engineer role at Capco?

A: For the Data Engineer role at Capco, you need strong skills in big data tools like Hadoop, Spark, Kafka, and scripting languages such as Python, Java, or Go. Experience in data pipeline and workflow management tools, as well as SQL for data manipulation and validation, is also essential.

Q: Why should I join Capco as a Data Engineer?

A: Capco offers engaging projects with leading banks and financial institutions, a culture that values diversity, inclusivity, and creativity, and ample career advancement opportunities without a forced hierarchy. You'll work on impactful projects that transform the financial services industry.

Q: What kind of company culture can I expect at Capco?

A: Capco has an open and tolerant culture that values innovative thinking, diversity, and inclusivity. You'll find a supportive environment that encourages you to be yourself and grow both professionally and personally.

Q: How can I best prepare for the technical interviews at Capco?

A: To prepare for the technical interviews at Capco, practice solving coding problems and revisit key data engineering concepts. Utilize resources from Interview Query to practice technical questions and ensure you're comfortable with tools and technologies mentioned in the job description.

Conclusion

Joining Capco as a Data Engineer offers a rewarding opportunity to work on transformative projects with some of the biggest names in the financial services industry. Despite some minor setbacks like delays in communication and technical hiccups with tools, the interview process is thorough and designed to ensure a good fit for both the candidate and the company. Capco values diversity, inclusivity, and innovation, making it a vibrant workplace where your unique contributions are recognized.

Capco’s commitment to career advancement, inclusive culture, and challenging projects can help you carve out a significant niche in the data engineering landscape. With Capco's diverse work environment and ample opportunities for growth, it's more than just a job – it's a career where you can thrive.

If you want more insights about the company, check out our main Capco Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as Senior Data Engineer and Data Analyst, where you can learn more about Capco’s interview process for different positions.

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 Capco interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!