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Giancarlo N.
Verified Expert
Senior Data Engineer
UTC-3 Argentina8 years of experience
Giancarlo is a seasoned data engineer with experience in structuring, developing, and maintaining ETL/ELT pipelines for big and small data, data lakes, and web scraping systems. He showcases extraordinary communication skills and is always willing to go a step further to anticipate and address potential issues.

Igor F.
Verified Expert
Senior Data Engineer
UTC-3 Brazil5 years of experience
Igor is a software engineer specialized in data engineering. He is proficient in programming, architecture, and database concepts. He is a proactive team player with critical thinking skills that will be valuable in any team.

David P.
Verified Expert
Senior Data Engineer
UTC-3 Uruguay5 years of experience
David is a Data Engineer with extensive experience in designing and implementing data-driven systems, from architecture to development. Known for his patience and persistence, he is a collaborative team player with exceptional analytical and logical thinking skills.
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Interview Questions
Learn everything you need to hire top-performing Data Engineering Experts. Our interview guide, crafted by industry experts, gives you crucial questions you should ask candidates to make the best hiring decision.
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Read moreThe BEON.tech Advantage
Why Leading Companies Choose Us
for Hiring Elite Data Engineering Experts.
Why settle for average local talent when you can access the elite? Get access to a pool of highly skilled LATAM professionals with specialized expertise in Data Engineering.
Don't wait for too long to fill critical roles. Get matched with qualified Data engineers in 24-48 hours to keep your projects on track.
Reduce costs by 30%-50% with top-tier Data Engineering Experts from LATAM—an efficient, budget-smart alternative to U.S. resources. Achieve high-quality results at a fraction of the cost compared to hiring locally.
Enjoy peace of mind knowing all local regulations, contracts, and labor laws are taken care of, ensuring full compliance in every aspect of the hiring process.
Collaboration just got easier. With professionals in similar or overlapping time zones, you can ensure seamless communication and faster turnaround times.
We don't believe in short-term fixes. With our Talent Experience Management™ Framework, we ensure long-term retention, professional growth, seamless team integration, high performance, strong engagement, and continuous upskilling.
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5 Must-Ask Data Interview Questions & Answers for Hiring Top Engineers
5 Must-Ask Data Interview Questions & Answers for Hiring Top Engineers
Looking to hire skilled Latin American Data Engineers? You're not alone. The US Bureau of Labor Statistics projects the number of jobs in the field to increase by 8% between 2022-2032.It's no wonder businesses everywhere are competing for top talent.
However, finding the right candidates starts with asking the right questions. That's where we come in. This article highlights 5 key Data interview questions we use at BEON.tech to identify the top 1% of engineering talent across Latin America, helping companies connect with the best.
Essential Data Interview Questions Every Recruiter Should Ask + Answers
Evaluating Data expertise isn't just about checking resumes, it's about understanding how candidates think, code, and solve real-world challenges. The right interview questions help you assess problem-solving skills, architecture decisions, and practical coding abilities.
We've curated five key technical questions that strike the perfect balance, challenging enough to gauge expertise without being overly theoretical. These questions will help you pinpoint advanced professionals who can contribute high-quality code and seamlessly integrate into your team.
Keeping that in mind here are some advanced Data interview questions for spotting higher seniority levels:
What are Common Mistakes to Avoid When Interviewing a Data Engineer?
Now that we've covered the must-ask questions for hiring a high-level Data Engineer skilled in optimizing queries, let's explore common mistakes that could derail your Data hiring process:
1. Overlooking Soft Skills
It's easy to focus solely on technical skills, but neglecting soft skills like cross-functional coordination can backfire. Data Engineers working on, for instance, real-time data processing systems or large-scale ETL pipelines often need to collaborate within a large team, communicate ideas clearly, and respond positively to feedback. Without strong cross-functional coordination, even the most talented Data Engineer may struggle to connect with the team. This can lead to divergent visions, sluggish workflows, and lack of synchronization.
2. Ignoring Cultural Fit
Hiring someone who doesn't align with your company's culture or remote work environment can lead to low engagement, poor collaboration, and high turnover. Employees perform best when their personal work style and values complement the company culture. Prioritizing cultural fit during the hiring process ensures tighter team synergy, clearer communication, improved job happiness, and lasting retention.
3. Neglecting Real-World Problem-Solving
Focusing solely on theoretical tests often misses an essential aspect—how a candidate handles practical challenges in specific areas. While technical quizzes can be helpful, they don't reveal how a candidate thinks through and solves problems in real-world scenarios. This oversight could result in low engagement, poor collaboration, and high turnover.
4. Failing to Assess Adaptability
The tech landscape evolves rapidly, and Data is no exception. If a Data Engineer isn't open to learning new tools or frameworks, they may struggle to keep up as the industry changes. Prioritizing adaptability ensures your hire will grow with your team and remain effective in navigating evolving challenges.
5. Rushing the Hiring Process
One of the costliest mistakes is rushing to fill a position, especially when the goal is establishing a high-efficiency team. Making hasty hiring decisions often leads to mismatches in skills or work style, causing disruptions in team dynamics and project delays. Taking the time to thoroughly vet candidates helps ensure the right fit, saving time and resources in the long run.
Key Takeaways
A well-structured interview process makes it easier to identify Data Engineers candidates who excel in technical expertise and team collaboration. By asking the right questions and evaluating both technical and soft skills, you can build a stronger, more cohesive team.





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