A Comprehensive Guide to Hiring the Best ETL Developers

You’re looking to hire an ETL developer, and you need someone who can actually deliver. Someone who can build reliable pipelines, handle messy data, and keep your reporting infrastructure running without constant handholding.

The challenge isn’t understanding the value of the role. It’s knowing how to hire the right person for it. From scoping the role to screening for technical and soft skills, the hiring process can easily go sideways if you’re not clear on what matters most. 

Whether you’re hiring in-office, remotely in the US, or internationally, the fundamentals stay the same, and we’re here to help. 

This guide covers how to hire ETL developers effectively, skills to look for, where to find qualified talent, real cost expectations, valuable interview questions, and common missteps to avoid.

What Do ETL Developers Do?

ETL developers build and maintain systems that move data from raw sources into structured, usable formats for analysis and reporting.

ETL stands for Extract, Transform, Load—the process of pulling raw data, cleaning and formatting it, and loading it into data warehouses or other storage platforms.

They play a critical behind-the-scenes role in ensuring data is accurate, consistent, and usable across the business. Done right, this turns fragmented data into actionable insights that teams across the business can rely on.

Without well-built ETL workflows, dashboards break, reports become unreliable, and data teams lose trust in what they’re working with.

ETL developers typically work alongside data engineers, analysts, and business intelligence teams—but their main focus is the flow and transformation of data, not infrastructure or analytics.

How Much Does It Cost to Hire an ETL Developer? 

Skilled ETL developers are in high demand, and their salaries reflect it. In the US, hiring for this role can be expensive, especially in competitive markets or when you’re looking for developers with cloud experience and deep SQL expertise.

Here’s a general breakdown of typical US salary ranges by experience level:

• Junior: $68,000 – $141,000
• Mid-level: $82,000 – $163,000
• Senior: $100,000 – $219,000

These ranges can vary depending on your location, tech stack, and whether you’re hiring in-office or remote. But overall, competition for experienced ETL developers in the US often pushes salaries toward the top end of the range.

If you’re open to hiring offshore developers, there are often significant cost savings to be made—sometimes between 30–70%, depending on the country and market. Latin America, for example, offers a strong pool of ETL talent. From our experience, salaries in the region typically fall into the following ranges: 

These differences reflect local cost of living and market norms, not a difference in capability. And while Latin America offers strong time zone alignment for US teams, other regions like Eastern Europe and Southeast Asia are also popular options for hiring ETL developers internationally.

Wherever you decide to hire, being aware of regional salary benchmarks can help you stay competitive without overextending your budget.

What Skills Should You Look For When Hiring an ETL Developer?

Knowing how to hire ETL developers also means understanding which skills separate decent hires from great ones. Below, we discuss some of these key skills in more detail.

Hard skills (the must-haves)

Hard skills refer to the technical abilities an ETL developer needs to build and maintain data pipelines. Hiring teams typically look for these first.

• Proficiency in ETL Tools: ETL developers should have hands-on experience with widely used tools like Informatica, Talend, or Microsoft SSIS, which are used to build, schedule, and monitor data workflows. Ask developers about specific projects and which tools they’ve worked with in production environments.
• Strong SQL skills: SQL is central to querying and transforming data, so fluency here is non-negotiable. Candidates should be comfortable writing complex joins, CTEs, subqueries, and window functions. Technical interviews or take-home challenges can help assess real ability.
• Data modeling and warehousing knowledge: A solid grasp of star and snowflake schemas, normalization, and dimensional modeling is vital. ETL developers need to structure data in ways that are efficient for reporting and analytics. Ask candidates to describe how they’ve designed or worked with warehouses in past roles.
• Scripting language proficiency: Many ETL processes require some scripting for automation or data manipulation outside standard tools. Look for those proficient in using Python, Bash, or Perl. You can ask for code samples or walk through automation tasks they’ve completed.
• Experience with cloud platforms: As more companies migrate to the cloud, ETL developers need experience with services on AWS, Azure, or Google Cloud. Certifications can be helpful, but actual project experience speaks louder.
• Understanding of data quality and governance: ETL developers play a major role in preventing bad data. Ask how they validate data, handle schema mismatches, and enforce governance standards. Their approach to integrity checks can tell you a lot about their discipline and reliability.

What you expect in each of these areas will vary depending on the level you're hiring for.

Here's a quick breakdown:

This makes it easier to align your job description with realistic expectations—and helps you avoid accidentally writing a spec for a senior engineer when you're hiring for a mid-level role.

Soft skills (equally important)

Soft skills influence how developers relate to others, manage their time, and respond to unexpected challenges. These are harder to measure but just as integral to success.

• Problem-solving ability: Troubleshooting broken pipelines or messy source data is a part of the job, so a strong problem-solving mindset is a must. It’s the most in-demand soft skill among IT professionals globally for a reason. Focus on candidates who can walk you through how they approached complex technical challenges, not just the fixes they applied.
• Attention to detail: Data mismatches and silent errors can lead to inaccurate decisions. ETL developers need to spot issues before they become problems. You might ask about how they monitor pipeline accuracy or how they’ve caught bugs in staging before production.
• Effective communication: ETL developers often collaborate with data analysts, engineers, and business teams. Clear communication helps translate technical tasks into business outcomes. Pay attention to how candidates explain past projects or decisions during interviews.
• Adaptability: Data sources, tools, and priorities can change fast. Good developers are comfortable learning new platforms and adjusting on the go. Ask how they’ve handled changes to tools, team structures, or requirements mid-project.
• Time management: Many ETL tasks are deadline-driven, such as daily refreshes, scheduled reports, and ad hoc requests. Look for candidates who can juggle competing priorities and deliver on schedule. A strong candidate can elaborate on their workflow or how they coordinate handoffs with QA or analytics teams.

Nice-to-have skills (the differentiators)

Nice-to-have skills aren’t required to do the job, but they add value, especially in complex or fast-moving environments. These skills often set candidates apart.

• Experience with big data technologies: Knowledge of Hadoop or Apache Spark can come in handy when processing large datasets. While ETL developers aren’t big data engineers, familiarity with these tools can be a major plus in high-volume environments.
• Knowledge of data visualization tools: While not a core ETL skill, familiarity with Tableau or Power BI helps developers better understand how their pipelines are used and supports stronger collaboration with analytics teams.
• Familiarity with Version Control Systems (VCS): Using Git or other version control tools helps ETL developers manage changes, track errors, and coordinate more effectively with teams.
• Understanding of Agile methodologies: Many data teams now follow Agile workflows. Developers who know how to work in sprints, attend standups, and prioritize tickets tend to integrate more smoothly into cross-functional teams.
• Business acumen: ETL developers don’t need to be strategy experts, but a basic sense of how data supports business goals, like customer behavior, finance, or operations, can help them build smarter pipelines and spot meaningful trends or issues sooner.

Where Can You Find and Hire Great ETL Developers?

There’s no one-size-fits-all answer when it comes to choosing where to hire the right ETL developers or how. Each option has its own advantages. Let’s go over them.

Deciding between local, US-remote, or international talent

The first step is deciding how wide to cast your net when it comes to finding talent. ETL work can be done effectively from anywhere, so your decision essentially comes down to priorities like collaboration, cost, and availability.

• Local, in-office: A good choice if your team is office-based and values face-to-face collaboration. Local hiring can simplify coordination and onboarding, but it limits your talent pool. Hiring talent locally also tends to come at higher costs.
• US-based, remote: Broadens your reach while keeping culture and business practices aligned. However, the salaries you’ll pay will remain at US market rates, which can make scaling costly.
• International/offshore: Opens the door to a much larger talent pool. Many offshore ETL developers have strong technical experience and salary expectations lower than US hiresthose of . 

When hiring internationally, Latin America offers real-time collaboration, high levels of English fluency, and large pools of data talent.

Regions such as South and Southeast Asia and Eastern Europe also provide diverse talent pools with solid technical expertise and enable round-the-clock operations across multiple time zones. 

Choosing the right sourcing channel

Once you’ve decided where to look for talent—locally, remotely, or internationally—the next step is figuring out how you’ll find the right person. Your sourcing channel shapes not only the speed of your hire but the quality of candidates you’ll attract and how much effort you’ll spend vetting them.

Some companies jump straight to job boards or Upwork, while others lean on their network or partner with a recruiter. Each option has tradeoffs. The right one for you depends on the type of ETL role you’re hiring for, how fast you need someone in place, and how confident you feel in your technical screening process.

Here’s a quick look at the most common sourcing methods and when they work best:

If you’re hiring internationally—especially for the first time—working with a recruiting partner who specializes in ETL and data roles can make a big difference. It’s the fastest way to get aligned, skip the guessing game, and start interviewing candidates who are actually a fit (but will come back to that later on).

How to Hire the Best ETL Developers: Best Practices

Hiring an ETL developer isn’t just about ticking off a list of technical skills. The best candidates are the ones who can work through messy data problems, collaborate across teams, and keep critical workflows running behind the scenes, without constant oversight.

That kind of hire doesn’t happen by accident. It takes a clear, focused hiring process that helps you spot not just who can do the job, but who will actually thrive in the role.

Below, we break down the hiring process into three key stages with practical tips at each step to help you hire smarter and avoid common missteps.

Stage 1: Before and during sourcing

Define your needs 

Start by defining the exact technical skills and experience your ETL developer must have. Avoid expecting a “unicorn” who excels at every tool or platform.

Instead, identify core skills such as proficiency with specific ETL tools, strong SQL knowledge, and experience with cloud platforms if relevant.

Narrowing your focus helps you target candidates who fit the job rather than chasing an impossible mix.

Write a precise software developer job description

Your developer job description is your first impression, so make it count. For ETL developers, highlight tech stack priorities and include details about project types and the team structure.

Skip vague phrases like “must be a fast learner” and instead emphasize what day-to-day tasks look like. Concise but targeted descriptions attract candidates who are confident they’ll fit the role.

Stage 2: Screening and evaluation

Use role-specific assessments

Resumes and buzzwords won’t tell you how well a candidate can actually work with complex data systems. We always recommend a practical test—focused on real ETL tasks. It is one of the most reliable ways to evaluate fit.

Give candidates a short, role-relevant exercise that mirrors the kind of problems they’ll solve on the job. For example:

• Ask them to write a SQL query that transforms messy, inconsistent source data into a clean reporting format.
• Present a broken data pipeline (or logs from a failed job) and have them diagnose the issue and suggest a fix.
• Share a scenario where multiple data sources need to be merged, and ask them to outline how they’d structure the ETL process, including validation and error handling.
• Have them write or review a short script (e.g., in Python or Bash) used to automate part of the ETL workflow, like moving files or sending failure alerts.

Whether you run it as a take-home test or a live working session, the goal is the same: evaluate how they think through data problems, how detail-oriented they are, and whether their approach reflects good judgment for production environments.

Evaluate problem-solving and critical thinking

Problem-solving is key, especially since ETL developers often troubleshoot complex pipelines and data quality issues. During interviews, present scenarios like data inconsistencies or system failures and ask candidates to explain their approach.

Look for structured thinking, attention to detail, and creative fixes rather than rote answers.

Seek initiative and self-direction

Successful ETL developers take initiative to identify and resolve data inconsistencies or pipeline failures before they impact downstream systems.

For example, an ETL developer who shows ownership will proactively monitor job performance and optimize workflows without prompting. They’ll also document their processes clearly and communicate updates or potential risks to stakeholders early on.

During interviews, ask candidates to describe situations where they caught and fixed data problems independently or improved an ETL process independently. These examples reveal their ability to work autonomously and stay accountable. 

Stage 3: Making the offer and closing the deal

Offer competitive packages with relevant perks

Experienced ETL developers are in high demand, so making a good job offer is essential to attract top talent. Beyond salary, consider perks that resonate with this role.

For instance, a professional development budget for certifications on cloud platforms can be a big draw to those seeking training. Flexible working hours or the option to choose projects involving emerging data tools also appeal to developers eager to expand their skill set. 

Highlighting access to cutting-edge data infrastructure or participation in strategic data initiatives shows candidates that they’ll grow alongside your business. 

Move quickly once you find the right fit

Delays risk losing candidates to competitors. Once a promising ETL developer passes your evaluation, go ahead with the offer process.

Then, communicate timelines and next steps. Explain when they’ll receive the official offer, onboarding details, and initial contacts. Transparency and responsiveness reflect well on your company culture and set the tone for a smooth hiring experience.

Set up clear onboarding expectations

Before day one, share documentation about your data architecture, key ETL tools in use, and relevant data governance policies. Introduce your new hire to stakeholders such as data engineers, analysts, and business users who rely on their work.

Define clear goals for the first 30, 60, and 90 days, like mastering the primary ETL workflows, contributing to a data quality improvement project, or optimizing an existing pipeline. 

Well-structured onboarding helps new ETL developers hit the ground running and builds confidence on both sides.

Top Interview Questions for Hiring an ETL Developer That Reveal the Right Fit

A carefully planned interview is key in identifying ETL developers who not only have the technical know-how but also align with your team’s workflow and problem-solving approach.

By posing thoughtful, in-depth questions, you can delve deeper into a candidate’s experience, analytical skills, and adaptability.

Here are four interview questions designed to uncover the most suitable ETL professionals for your business.

“Can you walk me through a complex ETL pipeline you’ve designed or maintained? What were the challenges, and how did you address them?”

Look for detailed explanations of the pipeline’s architecture, data sources, transformation logic, and loading mechanisms. The candidate should articulate specific challenges and the strategies employed to overcome them.

What it reveals: This question assesses the candidate’s hands-on experience with intricate ETL processes and their problem-solving capabilities.

Red flags: Vague descriptions, lack of complexity in examples, or inability to discuss specific challenges and resolutions may indicate limited experience.

“How do you ensure data quality and integrity throughout the ETL process?”

Effective candidates will discuss implementing validation rules, error handling mechanisms, and data profiling. They might mention tools or scripts used for data cleansing and monitoring, as well as strategies for handling exceptions and ensuring consistency.

What it reveals: This probes the candidate’s commitment to maintaining high data standards and their familiarity with validation techniques.

Red flags: Overlooking the importance of data validation, lacking specific methods or tools, or providing generic answers without concrete examples.

“Tell me about a situation where you had to collaborate with cross-functional teams during an ETL project. How did you maintain alignment and succeed?”

Candidates with excellent communication skills will know how to engage with stakeholders, provide updates, and incorporate feedback. They should highlight their role in facilitating understanding between technical and non-technical team members and making sure that the ETL solutions meet business needs.

What it reveals: This question explores the candidate’s communication skills and ability to work collaboratively.

Red flags: Difficulty articulating collaborative experiences, lack of stakeholder engagement, or an overly technical focus without consideration of business objectives.

“How do you handle changes in source data structures that can impact existing ETL workflows?”

Look for strategies like implementing schema versioning, using metadata-driven ETL processes, or setting up alerts for schema changes. The candidate should demonstrate foresight in designing flexible ETL systems that can accommodate changes with minimal disruption.

What it reveals: This assesses the candidate’s adaptability and proactive approach to managing evolving data sources.

Red flags: Lack of awareness or strategies for handling schema changes or reliance on ad-hoc fixes rather than systematic solutions.

Common Mistakes to Avoid When Hiring ETL Developers

Even with a clear process, it’s easy to make the wrong call if you’re not careful about how ETL roles differ from other technical positions. Here are some common traps companies fall into—and how to avoid them. 

Assuming any data engineer can do ETL work

Not all data engineers have hands-on experience building ETL workflows—some specialize in infrastructure, others in modeling or analytics. If your job requires managing daily data flows, cleaning and transforming large volumes of data, or working with specific tools like SSIS or Talend, you need someone who’s done it—not just someone with a general “data” title.

A comprehensive understanding of different types of data engineering roles will help.

Treating SQL like a checklist item, not a core competency

Almost every ETL role mentions SQL, but few hiring processes actually test for depth. Writing basic queries isn’t enough. You want someone who can handle complex joins, CTEs, window functions, and performance tuning—because that’s where the real work happens. 

Overlooking the importance of error handling experience

Not being able to assess a candidate’s experience with error handling can result in fragile ETL processes that fail silently or cause data inconsistencies. Robust error handling is essential for maintaining data integrity and ensuring reliable data pipelines.

Inquire about past experiences dealing with errors in ETL processes. Ask candidates to describe how they have implemented error detection, logging, and recovery mechanisms in previous projects.

Neglecting the need for documentation skills

When candidates are not evaluated for their ability to document ETL processes, maintenance, onboarding new team members, and troubleshooting can be challenging for the organization. Comprehensive documentation promotes continuity and efficiency in data operations.

Request examples of documentation from previous projects or ask candidates to explain how they document their work. 

Why Working With a Recruiting Partner Makes a Difference

Hiring on your own can work, especially if you have the time, the network, and a clear idea of what you’re looking for.

But when you’re short on bandwidth, hiring for a highly specialized role like ETL development, or considering international candidates, working with a recruitment partner can save you from costly delays and mismatches.

Here’s how an expert recruiting partner can help:

• Faster access to qualified candidates: They have vetted networks and sourcing channels specific to technical roles like ETL development.
• Role-specific screening expertise: Recruiters familiar with data engineering know how to assess technical fit and not just keywords on a resume.
• Reduced time-to-hire: They keep the process moving behind the scenes, saving you weeks of back-and-forth and dead-end interviews.
• Better candidate experience: Consistent communication and clear timelines help keep top candidates engaged at every stage.
• Support for international hiring: If you’re looking to hire outside the US, recruitment partners that specialize in sourcing offshore talent can also handle compliance, contracts, and onboarding logistics.
• Less pressure on internal teams: Your team can stay focused on their core responsibilities while experts manage the hiring process.

A reliable recruiting partner, with their efficient hiring solutions, can help you make better hiring decisions faster and with less risk.

Final Thoughts

Hiring a great ETL developer isn’t just about checking technical boxes—it’s about finding someone who can build dependable systems, solve tricky data problems, and support smarter decision-making across your business.

Whether you’re building out your first data team or replacing someone in a high-stakes role, the hiring process needs to be intentional.

From defining the right scope, to knowing what skills actually matter, to avoiding common traps that waste time or lead to bad fits—getting this hire right makes everything downstream easier.

And if you’re open to hiring beyond your local market, you’ll have a serious advantage. Companies that tap into nearshore talent—hiring in countries in Latin America—often find experienced, highly motivated ETL developers with salary expectations at a fraction of a US-based hire, without sacrificing quality or collaboration.

Finding that kind of talent is what we do at Near.

We present you with vetted ETL developers in Latin America—folks who are aligned on time zones, fluent in English, and ready to make an impact fast.

Our comprehensive, personalized approach matches ETL developers not just to your technical requirements but to your team culture and working style, reducing the risk of mis-hires and helping you build a high-performing data team quickly and cost-effectively.

If that sounds like the support you need, book a free consultation call and let’s talk through your hiring goals.