Hiring Remote Data Engineers: 6 Things to Consider
Every successful data-driven business relies on its data engineers. It can be expensive to hire data engineers onsite, but there’s a better way to do it. The rise of the gig economy creates a niche for remote data engineers who bring their skills to the table for everyone.
You can find some of the best remote data engineers halfway across the world. If you’re looking to improve your business intelligence, consider x things when hiring data engineers.
1. Set Remote Position Expectations
The success of a remote position depends on your ability to define the expectations clearly. The best remote work arrangements have trust as the central component. Communication is also crucial, as you want your employee to give you consistent updates about their progress.
When hiring data engineers, it’s crucial to understand the different types of roles available. Data engineering requires specific skills from a developer’s perspective. Consider whether you’re looking for a data engineer, a software engineer, or a machine learning specialist.
It’s also essential to define the volume of work. In general, these jobs require a minimum of 20 hours per week. The workload is consistent, but you might also receive additional projects.
Once you understand the project, you’ll have to agree on the work schedule. The time zone is also an essential factor.
2. Look For Talent In The Right Places
Finding talented employees is no easy task. The rise of the internet is a double-edged sword. On the one hand, it makes it easy to get in touch with anyone worldwide. On the other hand, it’s harder to filter through the noise and find the right people.
Many businesses look for developers in a variety of different places. There are numerous job boards online, especially for freelancers. However, if your project is complex, you should consider using larger platforms. There are also specialized platforms that specifically cater to data scientists.
Using a more conventional site, you get access to more candidates. You also get the opportunity to filter and sort according to your specifications. The downside is that you have to pay more, with the cost depending on the package you choose and the duration of the contract.
Start by looking for candidates in relevant communities. LinkedIn is perfect for finding people with the right set of skills. The data science community is a great place to find talent.
You can also host a few online interviews. The interview process can be time-consuming, and it might require some effort. However, it’s a crucial step in the hiring process.
3. Review Resumes and Portfolio
When you’re reviewing resumes and portfolios, focus on the experience. Look for candidates who have worked with big data in the past. The portfolio should also reflect the type of projects the candidate is working on.
For example, if you find a resume that mentions working on Apache Hadoop, you know they have the right skills and experience. At the same time, you want to look for relevant experience. You don’t want to hire someone who’s only working with relational databases.
Another thing to look out for is the skills and programming languages. You want to hire a candidate who has the right level of knowledge. Avoid candidates who don’t have a portfolio or have a sample code. Still, you might want to give them a chance to prove themselves if you like finding gems in the rough.
4. Build An Interview Strategy
The process of interviewing top talent takes time. The companies often spend months finding the right person. The process involves a background check, a phone interview, an in-person meeting, and a technical assessment.
When coming up with your list of interview questions, make sure the questions are relevant to your project. Don’t be afraid to ask the tough questions, as you want to weed out people who are incompatible with the project.
Technical evaluations are an essential part of the recruitment strategy. Data engineers need to pass a test that covers different skill sets. The candidates are also asked to explain their thought processes, state how far they have gotten on a task, and explain their approach.
5. Don’t Hesitate To Hire Remote Data Engineers Abroad
An international expert can be a valuable asset to your company. With the rise of data science, you can find outstanding experts in India, China, Brazil, or Southeast Asia. The best part about hiring a foreign candidate is you don’t have to pay for relocation. You can hire them and pay them remotely.
Regardless, when hiring a worker abroad, there’s always some risk. They might be unavailable when you need them, misuse resources, or not deliver quality work. You also have to consider both timezone and cultural diversity when hiring someone from a different country.
Hiring someone from a different country or in a different timezone can be challenging. Depending on the amount of communication, it can involve a lot of back and forth. This, in turn, increases the amount of time it takes to complete the tasks.
It can be stressful, but you can hire the best from all over the world. The benefits of outsourcing this work can be incredible. You might find someone who matches your expectations better than a local candidate.
6. Be Transparent
The relationship between you and your contractor is prone to misunderstandings. You’ll want to keep things clear to avoid any problems. The success of any collaboration depends primarily on the alignment of both parties. If you want your working relationship to be successful, you need to be transparent. You need to communicate openly and frequently.
Keep in mind that communication is key. One of the most important aspects of transparency is setting deadlines. Don’t underestimate the importance of a deadline, as it gives your consultants a clear schedule and helps you manage their workflow.
When communicating with your hired workers, you also have to be flexible. Your schedule might not always be the same, so give your contractor enough time to deliver the necessary results.
You also need to be clear about the deliverables. Having a deadline is one thing, but you also need to understand what you’ll get. Be realistic and set your milestones.
The Bottom Line
Finding the right talent for your data engineering team can be challenging. It’s difficult to sift through hundreds of applicants. If you have the time and the money, you can outsource the work to get the best results for an affordable price.
Hiring a qualified and skilled set of contractors has never been easier. From India to Eastern Europe to Southeast Asia, there’re plenty of options for finding a quality freelancer.
The key is to find the right person who fits right with your team. If you take your time and give the process some thought, you’ll quickly discover the best option for your business.
About the author
Chatty is a freelance writer from Manila. She finds joy in inspiring and educating others through writing. That’s why aside from her job as a language evaluator for local and international students, she spends her leisure time writing about various topics such as lifestyle, technology, and business.