How to Hire a Remote Data Engineer: Steps and Best Practices

Data engineers set up the systems that collect and organize data so businesses can make sense of it and use it to make better decisions.

And while data engineering might sound like something only large enterprises need, that’s not the case—businesses of all sizes can benefit.

While finding the right data engineer can be a challenge, you don’t have to limit your search to your local area. Hiring remote data engineers expands your options, letting you access a wider talent pool. But how do you do it right?

In this guide, we’ll walk you through how to hire a remote data engineer and provide practical tips for hiring.

What Is a Data Engineer?

Data-driven companies are 23 times more likely to acquire new customers and 19 times more likely to remain profitable. How? By optimizing decisions and strategies based on concrete data.

But for this to work, businesses need reliable, well-organized, and easy-to-access data—something a data engineer can provide. A data engineer transforms raw, scattered information into structured data pipelines that drive business insights. 

They often need a background in fields like computer science, software development, and information systems, as their key responsibilities include:

• Creating systems that automate data flow from various sources to databases or cloud storage
• Ensuring data quality by cleaning and validating information
• Optimizing storage, speed, and scalability for growing data needs
• Collaborating with analysts, developers, and data scientists to meet business goals

If you aren’t sure you need a data engineer, read our articles about the benefits of hiring a data engineer and how they can help growing businesses.

What Are the Different Types of Data Engineers?

All types of data engineers are expected to handle data, but their tasks vary depending on their roles. 

Here’s a quick breakdown of various data engineering roles and what they do:

• Data pipeline engineer: Builds and maintains systems that transport data from various sources to storage or processing platforms and extract, transform, and load (ETL) frameworks.
• Data warehouse engineer: Responsible for implementing and maintaining structured storage systems like Snowflake and BigQuery for fast data retrieval. A data warehouse architect might be a good fit for strategic storage design. 
• Data infrastructure engineer: Builds and maintains the core architecture for data storage and processing. They often use cloud platforms, Kubernetes, and Terraform to support seamless data operations.
• Data quality engineer: Focuses on data accuracy and consistency by developing validation processes and automated testing frameworks to minimize errors.
• Data DevOps engineer: Bridges data engineering and development and operations (DevOps) by automating deployments, monitoring pipelines, and optimizing workflows through CI/CD tools and infrastructure automation.
• Machine learning (ML) data engineer: Prepares and optimizes data for use in machine learning projects. They collaborate with data scientists and use frameworks like TensorFlow and PyTorch.
• Security data engineer: Protects sensitive data by implementing encryption, access controls, compliance measures to meet regulations like GDPR and HIPAA, and data loss prevention. 

Key Skills You Need to Look For When Hiring a Remote Data Engineer

Whether you’re hiring a full-time remote employee or a freelance data engineer for short-term projects, prioritizing the most important skills—and they’re not just technical ones—can help keep your data systems efficient, scalable, and aligned with business goals.

Key technical skills for remote data engineers 

Technical skills are the driving force behind data engineering, enabling efficient data processing, storage, and transformation with minimal supervision. 

• SQL and database management: A skilled data engineer can use SQL with databases like PostgreSQL, MySQL, and SQL Server to extract, manipulate, and organize data efficiently.
• ETL and data pipeline development: All data engineers need to be able to build ETL pipelines to automate how raw data moves from one system to another. 
• Programming skills: Coding automates tasks, transforming data, and integrating different systems. A proficient data engineer should be comfortable with programming languages like Python, Scala, Java, and Bash (Shell). They don’t need to know all of them, but Python is usually a must-have. 
• Cloud computing and storage: Cloud data engineers often specialize in particular platforms, so you’ll need to look for relevant expertise depending on your tech stack. For example, a remote Azure data engineer can manage ETL pipelines with Azure Data Factory, optimize storage with Azure Blob Storage, and improve performance using Azure Synapse Analytics.
• API integration and web scraping: Data engineers skilled in API integration and web scraping can help your business collect valuable external data, even more so when you rely on timely data.

Aside from these core skills, there are other nice-to-have technical skills that may not be required for every hire but can offer extra value—especially if your business handles large-scale data or complex analytics.

• Big data technologies: If your company deals with massive datasets, you’ll want a remote big data engineer who understands the tools for processing, storing, and analyzing big data.
• Machine learning integration: While data scientists typically manage ML workflows, engineers familiar with ML concepts can better support AI-driven projects. 

Key soft skills for remote data engineers 

Soft skills are just as important as technical know-how, especially for remote data engineers who work without in-person supervision.

• Excellent problem-solving: Engineers who think on their feet can fix issues quickly, prevent delays, and keep your data systems running like clockwork.
• Good communication: Effective written and verbal communication is vital for remote engineers. Excellent communication skills help explain complex ideas in simple terms so the whole team stays on the same page.
• Effective collaboration and teamwork: Even though they are miles away, remote engineers shouldn’t be working in a bubble. They should be able to collaborate with various teams and departments to make sure data flows smoothly across your organization.
• Attention to detail: In data engineering, the small stuff matters. A tiny error in a query or pipeline can cause big problems. Detail-oriented engineers are more likely to catch mistakes early and keep your data accurate.
• Adaptability: Tech moves fast, and adaptable engineers move with it. They stay ahead by learning new tools and techniques, keeping your data systems up-to-date and ready for whatever comes next.

• Self-management: Without a manager sitting nearby, remote engineers need to stay on track by themselves. Self-motivated hires can manage their own workload, hit deadlines, and keep projects moving forward. Engineers with effective time management for remote work know how to prioritize, avoid bottlenecks, and keep things running smoothly.

To assess these abilities more effectively, consider using behavioral interview questions to explore past experiences and role-playing scenarios to observe real-time responses.

We have a list of 15 questions to ask remote workers that will help you uncover some of the soft skills mentioned above.

Where to Hire Data Engineers

Choosing a data engineer requires considering both geographic location and the platform or method you’ll use to find the right candidate.

Location to source from

When hiring remotely, you have two main options: hiring US-based remote talent or expanding your search globally.

US-based remote hiring gives you the familiar benefits of shared time zones and cultural context, but you’ll still face the same talent shortages and high salary expectations that prompted you to consider remote hiring in the first place.

Going global opens up significant advantages:

• Expanded talent pool: Access to specialized skills that might be scarce in the US market.
• Cost savings: Depending on the region, you can save 30–70% on salary costs without sacrificing quality.
• Time zone flexibility: With the right approach, you can either create 24/7 coverage or ensure substantial overlap with your workday.

For US companies looking to maximize these benefits while minimizing potential drawbacks, hiring data engineers in Latin America (LatAm) offers an ideal balance. You’ll get:

• Real-time collaboration: Most LatAm countries share time zones with the US, enabling seamless communication during regular business hours.
• Significant cost savings: LatAm data engineers typically have salary expectations 40–60% lower than their US counterparts with comparable skills.
• Strong technical education: Countries like Brazil, Argentina, and Mexico have excellent technical universities producing top-tier data talent.
• Cultural alignment: LatAm professionals often have experience working with US companies and understand American business practices.

Curious about how US salaries compare to LatAm salaries? Check out our salary guide for various data roles to see the difference.

Hiring methods

Once you know where you want to source candidates, the next decision is how you’ll hire them. This depends on how hands-on you want to be during the process.

Here are some common hiring methods to consider:

• Freelance platforms: Sites like Upwork and Fiverr are great for finding freelancers if you have short-term or project-based needs.
• Job boards: Posting on LinkedIn or Indeed puts you in the driver’s seat. You’ll manage everything from screening to interviewing, which gives you full control but takes significant time.
• Personal recommendations/network: Sometimes, the best hires come from trusted recommendations. It’s always worth tapping your existing connections before casting a wider net.
• Recruitment or staffing agencies: Partners who handle the heavy lifting—from sourcing and screening to shortlisting candidates who match your specific requirements.

Working with a recruitment agency is particularly useful when you’re hiring remote talent from outside the US. Agencies provide access to pre-vetted candidates and streamline the hiring process for a smoother, faster, and less stressful experience—especially if you’re new to hiring from a global talent pool.

Full disclosure—we’re obviously biased here since this is exactly what we do at Near. But we’ve seen firsthand how partnering with experts who understand the LatAm market transforms the hiring process for our clients. Instead of spending weeks posting jobs, filtering resumes, and trying to assess English proficiency or decipher unfamiliar educational credentials, you can focus on evaluating a handful of pre-vetted candidates who actually fit what you’re looking for.

The right partner doesn’t just save you time—they help you navigate cultural nuances, compensation expectations, and compliance issues that might not be on your radar. When you’re hiring internationally, these details make the difference between landing an A-player who sticks around versus starting the whole process over in three months.

5 Practical Tips When Hiring Data Engineers Remotely

Hiring data engineers remotely requires careful planning for a successful process. Whether you’re hiring from within the US or exploring offshore talent, these practical tips will help you get it right.

1. Don’t focus solely on costs: Lower rates can be tempting, but prioritize value over price. Look for candidates who offer the best mix of skills, experience, and long-term potential.
2. Find the ideal hiring partner: This depends on your needs, such as whether you want minimal involvement or help with specific stages like sourcing or screening.
3. Be clear on your remote work setup: Be ready for remote collaboration with a remote work plan that covers time zone management, communication tools, and performance tracking.
4. Conduct thorough interviews. Remote working is different from in-person work, so remember to ask about their experience working remotely and include online technical assessments when necessary.
5. Communicate expectations up front: Set clear expectations around working hours (especially when time zones differ), deadlines, and status updates/collaboration methods to avoid misalignment later on.

How to Hire Remote Data Engineers

If you decide to handle the hiring process yourself instead of working with a recruitment partner, you’ll need to manage each step of the journey.

This DIY approach works best for businesses with in-house recruiting expertise, enough bandwidth to manage the process, and some familiarity with the challenges of remote hiring.

Going it alone gives you complete control but requires significant time investment—from crafting the perfect job description to handling international payment logistics if you are hiring offshore.

Here’s a step-by-step guide for those taking the independent route:

1. Define your requirements clearly

Start by figuring out exactly what you need from a data engineer. Define the role’s scope, the key skills they’ll need, and the kinds of projects they’ll be working on. The clearer you are, the better your chances of finding the right match.

2. Set your budget

Decide how much you’re willing to spend on the hire. If you’re hiring internationally, keep in mind that salaries also vary widely by region.

Don’t forget to factor in things like software or any potential compliance and legal costs. 

3. Post your job 

Once you’ve written a comprehensive remote job description, it’s time to post it on various job boards. To stand out, highlight why your company is an ideal place to work, the perks of the role, and what makes the job exciting.

4. Sift through and screen resumes

Here, you’ll start narrowing your list of candidates. Once applications start rolling in, look for ideal candidates with relevant technical skills, remote work experience, and any specific tools or qualifications needed. 

5. Conduct technical assessments

These assessments help ensure your top candidates have the right technical chops. Assessments can include coding tests, SQL challenges, or data pipeline exercises. Tailor the assessment to match the actual work they’ll be doing. 

6. Conduct interviews

Interviews give you a chance to evaluate communication skills, problem-solving ability, and cultural fit. Ask about their experience working remotely, how they manage their time, and how they handle teamwork across different time zones.

7. Make an offer and sign a contract

Found a great fit? Make a detailed offer that includes the salary, benefits, and any remote work expectations. If you’re hiring internationally, ensure the contract covers important legal details. 

Platforms like Deel or Remote can make international payroll and contracts much easier to manage.

8. Onboard

Onboarding is your chance to help your new hire hit the ground running. Since they’ll be working remotely, it’s a good idea to set effective goals right away so everyone knows what to expect. Regular check-ins during the first few weeks can also help them feel more connected and supported.

Final Thoughts

Hiring remote data engineers is completely doable on your own—especially if you’re focusing your search within the US.

With the right process in place, you can find solid candidates who bring the technical skills and remote work capabilities your business needs. 

But if you’re looking to truly maximize your hiring potential, expanding your search internationally opens up access to a much deeper talent pool while potentially saving 30–70% on salary costs. But that’s where the complexity increases.

Navigating unfamiliar job markets, evaluating international credentials, handling compliance issues, and managing cross-border payments can quickly turn a straightforward hiring process into a time-consuming project of its own.

We even have a more in-depth remote hiring guide you can use to shape your strategy, but working with a specialized partner who knows an offshore market inside and out drastically simplifies this process.

Instead of building an international hiring system from scratch, you get immediate access to pre-vetted talent that matches your specific requirements—often filling critical roles in weeks rather than months.

If you’re ready to explore how LatAm talent could transform your data engineering capabilities, consider Near. We connect US mid-market enterprises and fast-growing startups with top remote LatAm data engineers who combine cost efficiency with specialized expertise across a wide range of industries.

Fill out this form to receive a list of pre-vetted candidates you can interview for free.