Key Takeaways
- The key difference between a data architect and a data engineer lies in focus: architects handle strategy and system design while engineers build and maintain data infrastructure.
- Businesses building a new data foundation should start with a data architect, while those with existing systems often benefit more immediately from a skilled data engineer.
- Data architects and engineers work best as a team, but in smaller companies, one person may temporarily fill both roles until the business scales.
Ever feel like you need a translator just to hire the right data expert? You’re not alone. The difference between a data architect and a data engineer might sound like a minor technicality, but it can make or break how your business handles data.
One sketches out the blueprint, and the other builds the system. Easy enough, right? Well, not always.
If you’re unsure who you actually need on your team, this guide will help you figure it out. We’ll explain what each role does in plain English, how they work together, and how to figure out which one fits your current goals.
What Is a Data Architect?
Think of a data architect as the city planner for your data infrastructure. They don’t lay the bricks themselves, but they decide where the roads go, how the buildings connect, and what rules keep everything running smoothly. In plain terms, a data architect is the strategist behind how your company’s data is organized, stored, and accessed.
Their core responsibilities include designing data models, setting governance policies, and choosing the tools and technologies your business will use to manage data. This often includes decisions related to database development, such as selecting storage systems and structuring how data flows between them.
They focus on the big picture: scalability, security, and long-term planning. Unlike data engineers, they are not typically involved in daily coding or pipeline maintenance. Instead, they work closely with leadership and technical teams to create a solid foundation for others to build on.
The demand for data architects is gaining traction. The US Bureau of Labor Statistics expects a 9% increase in demand over the next decade. That may not sound dramatic, but it is still faster than the average for most occupations and signals steady growth.
If your business is starting from scratch or rethinking how data flows across systems, hiring a data architect could be the smartest first step.
What Is a Data Engineer?
If a data architect is the planner, the data engineer is the builder. Once the blueprint is ready, data engineers step in to make it real.
They create, maintain, and fine-tune the systems that move data from one place to another. They might build pipelines, connect APIs, or make sure databases talk to each other. Either way, they’re the hands-on problem solvers keeping everything running smoothly.
Their day-to-day work involves integrating data from various sources, transforming it into usable formats, and making sure that it’s accessible to analysts, scientists, and decision-makers. They work closely with languages and engines like Python, SQL, and Apache Spark, often writing code to automate data flows and maintain system performance.
Because so many businesses in the US are adopting AI and machine learning, the demand for skilled engineers is skyrocketing. In fact, data engineer roles are one of the fastest-growing tech jobs.
If you’re thinking about hiring, it’s worth knowing the different types of data engineers out there. Some specialize in building pipelines, while others focus on analytics or real-time systems. Understanding those differences can help you zero in on the right fit.
Data Engineer vs. Data Architect: The Key Differences
Hiring the right data professional starts with understanding how these roles actually differ. This applies not only to the title but to day-to-day impact. A data architecture vs. data engineering comparison reveals two distinct skill sets and focuses.
One focuses on planning, the other on building.
If you’re trying to decide who to hire first or whether you need both, this breakdown can help you make a smart, informed choice. Let’s look at how these roles compare across key areas:
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How their skills differ
While both roles require a strong foundation in data systems, their technical skill sets are quite different. A data architect needs to think strategically. They should be comfortable with system design, database theory, and long-term planning.
Architects often have experience with tools like dbt, ER/Studio, and enterprise cloud platforms. Strong communication is key because they need to align data systems with business goals.
Data engineer skills, on the other hand, involve hands-on experience with code and systems. They need to know how to build, test, and maintain data pipelines. Engineers often work with languages like Python and SQL, as well as platforms like Apache Spark, Airflow, and Kafka. They also need strong problem-solving skills to troubleshoot system issues quickly.
The skills overlap in some areas, but the emphasis is different. One is about structure and design. The other is about execution and delivery.
What do the roles look like in practice?
To see how these roles work in practice, picture a retail business launching a new analytics initiative.
The data architect plans how systems like the ecommerce platform, CRM, and inventory tools should connect. They define how customer data will be structured and how it should flow between systems.
The data engineer then builds the pipelines that pull sales data from Shopify, clean it up, and deliver it to a dashboard the marketing team can use.
Salary comparison
There’s also variation from a salary perspective, with data engineers in the US having a much larger salary range than data architects.
In the US, salaries range from $85,000 for a junior data engineer to $265,000 for a senior engineer.
But if you are open to hiring a remote data engineer, there are savings to be made. In our experience, data engineers typically earn between $42,000 and $84,000 in Latin America—making hiring for this role more accessible to smaller companies and startups.
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It’s a similar situation for data architects:
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These ranges reflect differences in role scope, experience levels, and demand in local markets.
Which Role Does Your Business Need? (Or Is It Both?)
Deciding between a data architect and a data engineer depends on where your business is in its data journey. If you are starting from scratch and need to build a strategy for how your data is structured, stored, and used, a data architect is the right first step. They will help you create a long-term plan that supports growth, security, and future analytics needs.
If you already have data tools or platforms in place, such as a CRM, a cloud data warehouse, or analytics dashboards, but your systems are not working well together, a data engineer may be all you need. Engineers can connect those systems, build pipelines, and make sure data flows cleanly and reliably.
If you are scaling up or modernizing older systems, you may benefit from hiring both. The architect defines the new structure. The engineer brings it to life.
Team size matters too. Smaller companies or early-stage startups sometimes hire one person to cover both roles. That can work in the short term, but it often leads to burnout or technical gaps. Larger companies usually separate these roles to improve focus and system quality.
Here are a few quick examples:
- A fintech startup with no data team hires a data architect to design an infrastructure that supports compliance and reporting.
- A mid-sized ecommerce business wants to connect its Shopify store, Google Ads account, and customer database. They hire a data engineer to build those pipelines.
- An enterprise retailer is moving from legacy systems to the cloud. They bring in both roles to lead the transition and avoid technical debt.
The right choice depends on your systems, your goals, and how fast you need to move. Knowing what each role offers makes the decision easier.
Final Thoughts
Data architects and data engineers both bring a lot to the table, but the right fit depends on where your business stands today. If you’re building from the ground up, planning a big change, or just trying to get your data to flow better, the role you choose matters.
The good news? You don’t need to be a tech expert to figure it out. You just need a clear sense of your goals and a bit of guidance.
That’s where we come in. At Near, we help businesses hire vetted remote data engineers and architects from Latin America and can even help you think through the structure of your team.
Book a free consultation call to discuss how we can help you hire for one or both roles within 21 days at 30–70% below US market rates.
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