Data steward: what they do, how much they earn, and how to become one

The data steward is the professional responsible for looking after the quality, standardization, and correct use of data within a domain of the company, such as customers, suppliers, materials, or products. They are the person who makes sure, day to day, that the data is clean, complete, free of duplicates, and ready to be used by those who depend on it. If you work with master records, data, governance, or operations and want to understand what a data steward does, how much they earn, and how to become one, this guide was made for you.

I will treat the topic the way I treat everything in data governance: without decoration, and without the idea that giving someone a new title is enough to solve the problem. In practice, the data steward is the function that sustains governance right where it actually happens, in the record, on the system screen, at the moment the data is created. And this is precisely the role most companies still treat as a second-class task.

What a data steward is

Data steward is an expression that translates roughly as a data administrator or curator. The word steward has that sense of someone who looks after something that belongs to someone else. And that is exactly what they do. The data steward is not the owner of the data, they are the guardian of that data's quality on behalf of the company and the areas that depend on it.

While concepts such as data governance, data quality, and Master Data Management describe the structure and the rules, the data steward is the one who makes all of it work in operations. They translate policy into practice. A rule that every supplier must have a validated CNPJ (Brazil's company registration number) only becomes reality when someone makes sure no supplier enters the database without that data. That someone is the data steward.

What few people realize is that this function was not born with a fancy English name. In many Brazilian companies, the data steward has existed for years under another job title: master data analyst, or person in charge of the material master. What changed was the understanding that this work is not data entry, it is governance. Whoever looks after master records is looking after the source that reports, purchasing, sales, and, more and more, artificial intelligence decisions come from.

What a data steward does in practice

The data steward's work revolves around making sure data is born right and stays reliable over time. They define and apply standardization rules, validate new records, fix wrong records, eliminate duplicates, track quality indicators, and serve as a bridge between the business area, which knows the data, and the technology area, which stores it. It is not a backstage role. It is a boundary role, in the middle of everyone who uses the information.

Let me give an example that shows up a lot in companies. The purchasing team needs to create a new material for an urgent requisition. With nobody looking after this, the buyer creates the item however they can, with a generic description like "large black screw". Weeks later, someone else creates the same screw again with a different description. Now there are two records for the same item. Inventory appears split, the consumption analysis is wrong, and the negotiation with the supplier loses strength because nobody sees the real purchase volume. The data steward is the one who prevents this from happening, by defining the description standard, reviewing the record at entry, and blocking the duplicate before it becomes a cost.

And here comes the connection I always make. The data steward does not work on guesswork. They need clear rules, a data dictionary that says what each field means, indicators that show where the database has holes, and a process that gives them the authority to say no. Without that, the data steward becomes just the person who puts out fires, fixing errors after the damage is done. With it, they start working on prevention, which is where data really improves.

Data steward, data owner, and data custodian: who is who

A common question is how the data steward fits among the other data governance roles. The data owner is the owner of the data within a business area, the person who answers for the rules and decisions of that domain. They are usually a manager, a coordinator, or a head, and they do not touch the data day to day. The data custodian is the one who looks after the technical side: infrastructure, database, security, and backups, generally someone in IT.

The data steward sits between those two worlds. They receive the business rules from the data owner and make sure they are followed in the real data, supported by the technical structure the custodian maintains. A simple way to remember: the data owner decides, the data custodian stores, and the data steward cares for. In more mature companies, there is also the Chief Data Officer coordinating the data strategy above everyone. The data steward is the operational piece of this machinery, and it is the one with the biggest shortage of qualified people in the market.

Where the data steward works: by data domain

In practice, there is no generic data steward who looks after everything. The work is organized by domain, because each type of data has its own rules. The supplier data steward understands CNPJ, vendor approval, and tax and banking data. The customer data steward handles the single view of the customer, prevents the same customer from showing up in three different forms, and cross-checks records from different areas. The material data steward masters taxonomy, classification, unit of measure, NCM (Mercosur Common Nomenclature, Brazil's tax classification code), and standardized description.

This division matters because good data governance requires knowledge of the business, not just the system. Nobody standardizes the MRO material master without understanding maintenance. Nobody organizes the supplier base without understanding purchasing and compliance. That is why the data steward usually comes from inside operations, from someone who already knows the pain of that domain. The best data steward is not the one who knows the most technology, it is the one who best understands what that data means to the people who use it.

Which tools the data steward uses

The data steward does not live on spreadsheets alone, although many companies still start there. As governance matures, they come to rely on tools that support the work. Master Data Management platforms are the center of this operation, because that is where the record is created, validated by workflow, and kept free of duplicates. In the market, the main ones are SAP Master Data Governance, Informatica, Stibo Systems, Reltio, Semarchy, Profisee, and Ataccama.

On the data quality side, tools such as Informatica Data Quality and Ataccama help measure, monitor, and clean the database continuously. To find and understand the data, data catalogs and metadata tools come in, such as Collibra, Alation, and Microsoft Purview, which help the data steward know where the information is and what it means. I mention these tools for information only, because the choice depends on context. The right tool is the one that solves the company's real problem, not the trendiest one on the market. And here is a reminder I always repeat: no tool does governance on its own. Without the data steward behind it, applying rules and judgment, the software only organizes the error faster.

How to become a data steward

There is no mandatory degree to be a data steward, and that is good news, because it opens the door to people with different profiles. I see three backgrounds that work very well. Master data and operations professionals, who already know from the inside where data is born and how it gets disorganized. Professionals from business areas, such as purchasing, supply chain, and finance, who understand the meaning of the data. And data and technology professionals who want to move away from the purely technical and get closer to the business.

The study path involves mastering the fundamentals of data governance and Master Data Management, understanding the dimensions of data quality, learning to organize taxonomy and standardization, and having a grasp of LGPD (Brazil's General Data Protection Law), since a good part of the data the steward looks after is personal data. On the certification side, the most internationally recognized is DAMA's CDMP, based on the DAMA-DMBOK guide, which builds the conceptual foundation for all data management. A bit of SQL also helps a lot, because it lets the steward check their own database without depending on anyone.

But the skill most lacking in this market is not in any certification: it is knowing how to talk to people. A good data steward sits down with the buyer, the warehouse staff, the financial analyst, and IT, and gets everyone to agree on a standard. They negotiate, explain the reason behind the rule, and show the impact of bad data in business language. Someone who only knows how to point out errors creates resistance. Someone who knows how to engage the areas around quality becomes indispensable.

How much they earn and what the opportunities are

Demand for data stewards has grown along with the perception that bad data is expensive and that artificial intelligence only works on a reliable foundation. That raised the value of the function. In Brazil, the pay of a data steward, often advertised as data governance analyst or master data analyst, tends to vary quite a bit depending on seniority and company size, going from entry-level ranges for those starting out to much higher figures for mid-level and senior positions with broad scope and responsibility for critical domains.

The value rises as the professional accumulates business knowledge, command of MDM tools, and the ability to lead the standardization of an entire database. More regulated sectors and companies with large purchasing and supply chain operations tend to pay more, because the impact of wrong data there is greater. It is a growing career, with more demand than supply of truly prepared people, and with a clear path of progression. From data steward to governance coordinator, from coordinator to data manager, and from there to leadership positions such as Chief Data Officer. Few areas offer such a clear track for those who start at the base of operations.

Main questions about the data steward

Is a data steward the same thing as a master data analyst? Not exactly, but that is usually where they come from. The master data analyst executes the record. The data steward takes on responsibility for the quality, standardization, and governance of that data. Many data stewards started as master data analysts and evolved by broadening their business and governance vision.

What is the difference between a data steward and a data owner? The data owner is the owner of the data within the business area and answers for the rules and decisions of that domain. The data steward is the one who looks after quality and standardization day to day, applying those rules to the real data. The owner decides, the steward cares for.

Do I need to know how to code to be a data steward? No. The data steward is a governance function, not a development one. Knowing a bit of SQL helps in checking the database, but the most important thing is to understand the business, the meaning of the data, and how to talk to the areas.

Does a data steward need a certification? It is not mandatory, but it helps. DAMA's CDMP certification is the international reference in data management. More than the certificate, what counts is knowing the fundamentals of governance and having real experience with a data domain.

Does the data steward work alone? No. They work in a network, connecting the data owners in the business areas, the technical team that supports the systems, and the users who consume the data. A good part of the work is coordination and alignment between people, not just correcting records.

MDM Academy: where governance trains the data steward

There is one point I want to make clear for anyone thinking about this career. The data steward is the function growing fastest in importance and the one with the fewest prepared people in Brazil. Companies need this professional, but almost nobody truly teaches how to look after a data domain in practice. And that is why MDM Academy exists.

MDM Academy is 4MDG's school of governance and master data, created to train the professionals the Brazilian market needs and cannot find. We teach data governance, Master Data Management, data quality, record maintenance, and standardization, in practical language and with real project examples, not textbook theory. For those who want to be a data steward, moving from executing records to taking on the governance of a domain is exactly the leap the training helps make.

If that is the path you want to follow, get to know MDM Academy and join the Data Club. It is where we exchange knowledge, discuss real cases, and train the next generation of data professionals in Brazil.

Conclusion

The data steward is one of the most strategic and most underrated functions in data governance. Strategic because they are the one who makes sure, at the exact point where data is born, that the company can trust its own information. Underrated because many people still see this work as bureaucratic record-keeping, when in fact it is the foundation of everything that comes after, from the report to the artificial intelligence decision.

If you want to enter this field, start looking at master records with different eyes. Every record you standardize, every duplicate you eliminate, every rule you get an area to respect is governance actually happening. That is the perspective that turns a master data analyst into a data steward, and a data steward into a central piece of the company's data strategy. The market is looking for these people. The question is whether you will be prepared when the opening appears.