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Being a Data Quality Analyst: Careers in Data Quality

If you’re considering the career opportunities available in data quality, data quality analyst is one of the more obvious titles to look at. But don’t be misled by the data… analyst part; there’s a lot more to the job than you might expect.

Here’s a deep dive into the role of a data quality analyst, and how you can tell if it’s right for you.

Qualifications

What kind of background do you need for data quality analysis? Here’s a rundown.

Education

Like most data-adjacent jobs, data quality analyst positions generally require a college degree; some companies specifically look for a B.S. But you don’t need a specific degree to have a chance.

If you have work experience in data analysis or a data-analysis-adjacent position, highlight that first on your resume, no matter what degree you have.

But if you’re a fresh graduate or changing fields, you might need to feature your degree more prominently, and that’s where knowing how to frame it will come in handy.

Skills

As a data quality analyst, you’ll need a combination of hard and soft skills. Don’t be misled by most of the words being data analyst; the soft skills aren’t just lip service confined to the job posting.

The hard (as in quantitative, not as in difficult) skills are the more obvious ones:

The soft (as in qualitative, not as in easy) skills are less obvious, but they’re extremely important in a successful data quality program:

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Personality

Becoming a data quality analyst isn’t the right path for everyone, even if your education and skills seem to line up—and if it isn’t for you, no shame in that! It’s better to know from the start if your preferred work style is compatible with the role.

To start, data quality analysts need to be very flexible. Check out these phrases from some real DQ analyst job postings:

Data quality analyst job posting excerpts: Proven ability to adjust quickly to shifting priorities, multiple demands, ambiguity and rapid change. Strong communication skills, a strong team player; able to accept and deliver ambiguous tasks. Strong multitasking skills, with the ability to work on multiple, concurrent projects and adapt to changing priorities in a fast-paced, high-growth environment.

OK, those phrases aren’t uncommon in job postings of all sorts. But that doesn’t make them less relevant for the data quality analyst role. “Data quality” is a new enough field that even long-term programs can suddenly find themselves needing a change.

If you strongly prefer to have a well-defined, long-term plan with few deviations and tightly-scoped work with clear boundaries, you probably won’t enjoy being a data quality analyst much.

On the other hand, if you like the variety that comes with moving targets, or appreciate the opportunity to define your own path that comes with not-very-well-defined goals, you can find those in data quality analyst roles.

To be a data quality analyst, you need to be comfortable working with people. Remember the importance of relationship-building: you’re going to be more successful if you’re proactive at forming those relationships, rather than doing only the absolute minimum.

You don’t have to be the most extroverted person to ever extrovert. But not all communication is best done over email, so if you’ll do anything to avoid getting on the phone or setting up a meeting, maybe this isn’t the right path for you.

As a data quality analyst, you’ll have to present results to groups, speak up unsolicited when you have relevant information, and advocate for yourself and your projects to get resources.

That might mean contradicting or correcting people who are senior to you in terms of the company hierarchy and/or tenure at the company. If that’s something you struggle with, be prepared to overcome it.

Advocating for resources can put you in direct competition with colleagues who want those resources for their projects. Whether you win or lose that competition, you need to maintain a working relationship with those people. Gloating and/or being a sore loser will be very unhelpful.

A tendency toward thoroughness is extremely valuable for data quality analysts. If a company is investing in their data to the point of hiring a data quality analyst, that data is now a valuable asset. And if it’s a valuable asset, you can’t be careless with it.

That means when you say you’re solving a problem, you need to solve it. If an edge case of the supposedly-solved issue pops up a week later, that’s going to look bad for you.

If you’re the kind of person who gets personal satisfaction from dotting every i and crossing every t, that expectation for deep-diving is a great fit. But if you’re happiest when you get the ball rolling then move on to the next thing, data quality analyst isn’t a good match.

You’ll also need to be comfortable, and ideally enjoy, explaining things. As a data quality analyst, you’ll be in the middle of a lot of different groups and working with people whose experience working with data is really variable.

You need to make sure all those people understand your conclusions, buy in, and execute the data quality solutions you develop. If you’re a patient teacher and comfortable thinking of different ways to explain the same subject, you’ll get to exercise those skills for sure. If you don’t like it when you have to repeat things, reformulate explanations, or when other people ask questions that are obvious to you, you’ll find this part of the role really frustrating.

Sometimes you’ll be on the other end of that scenario: an expert in a different area will be telling you something that you don’t really grasp right away. You need to be willing to ask questions and admit you don’t know or understand something if you want to extract a successful outcome from the situation.

Finally, as a data quality analyst, you’ll be working in a field that is very much still under development. There are established frameworks for some situations and software vendors that have implemented a lot of functionality, but best practices are constantly being updated, and new techniques are always being invented.

Your personal experience will vary widely depending on how well-established your company’s data quality program is. You might find you have colleagues who have seen it (almost) all before as you work in a well-established framework. Or you might find yourself in the (metaphorical) wilderness, troubleshooting problems and creating procedures from an absolutely blank slate.

If you strongly prefer one or the other, look for roles accordingly.

Job Duties

We’ve covered many of the job duties of a data quality analyst in the course of the discussion above, but here’s a summary.

Data quality analyst job duties word cloud: data,data quality, data quality analyst, data quality issues, data sme, root cause, data source, development team, improvement opportunities, project plan, quality data analyst, subject matter expert, accuracy of data, analytical results, best practice, clinical quality measures, continuous process improvement, corrective action, critical datasets, customer data, data completeness, data governance report, data governance requirements, data integrity, data operations technology, data pipeline, data quality error, data quality management, data quality rules, data quality solutions, data visualization, detailed understanding, fraud waste, healthcare data sme, internal process, light development, operations team, process change, quality metric, statistical analysis, summarization techniques, team member, technical group, user acceptance testing, utilization management Word cloud generated using MonkeyLearn.

Type of Job

The most common type of data quality analyst role is permanent, full-time, and on-site.

However, there are some organizations that have partly or fully remote data quality analyst roles. These may start to become more common now that Covid-19 has forcibly introduced work-from-home into many companies.

While as of 2021 full-time is by far the most common job type for data quality analysts, there are some part-time positions. Again, as the data quality field grows, more part-time positions may become available as smaller organizations that can’t support a full-time data quality analyst still find the need for one, or as larger organizations look to supplement their existing teams.

Most posted openings for data quality analysts are for permanent employees, but there are contract and temporary positions available. These are usually associated with consulting firms, looking for a data quality analyst with experience in a specific industry to round out their in-house team for a specific project.

Data quality analyst job pie chart: Full-time 89.0%, Part-time 4.9%, Contract 4.6%, Other 0.5%, Temporary 0.9% Data compiled from LinkedIn, Indeed.com, and Glassdoor January 2021 Data quality analyst job pie chart: In-Office 92.6%, Remote 3.8% Data compiled from LinkedIn, Indeed.com, and Glassdoor January 2021

So, while most data quality analyst roles point to a typical office experience, there are some openings for people who are looking for shorter-term or remote work in the role.

Consulting-associated opportunities might be especially appealing if you’re a late-career professional who’s not quite ready to retire, but not looking for years-long commitment. If any of your work history is in the same industry as the project, but a non-data-quality position, this could position you as a very competitive candidate for these very specialized projects as long as you have the requisite technical skills.

Data Quality Analyst Salary

According to January 2021 data from Indeed.com, the national average salary for a “data quality analyst”-titled role is $62,453, with salaries ranging from $43K at the low end to $95K at the high end.

Comparing the eleven cities below, most fall in line with this national range, the exception being San Francisco and its famously high cost of living.

If you’re looking for data quality analyst salary information in a location where Indeed (or your research site of choice) doesn’t have much data for that title, try checking related job titles—discussed next—to get a better idea of what to expect.

Related Job Titles

If you’re searching for a data quality analyst job, keep in mind that there’s no universal definition of “data quality analyst.” It’s a relatively new role, so if an accepted definition does start to coalesce, it’ll probably still be a few years from now.

Today, roles that are data quality analyst roles, as described in this article, might be listed as business analyst, data analyst, IT analyst, data engineer, quality assurance analyst, and other similar titles.

You’ll note that these titles are heavily associated with the “hard skills” aspects of data quality analysis. You’re very unlikely to find data quality analyst jobs listed with more communications-oriented titles.

Industries

There’s potential to be a data quality analyst in almost any industry that uses data… which is all of them.

Industries which are “traditionally” known for heavy data usage include finance, telecommunications, health, and government.

Data quality analyst job posting examples: Data Quality Analyst (Data Analyst IV) at Texas Education Agency, Data Quality Analyst at Global Atlantic Financial Group, Enterprise Data Governance Data Quality Analyst at US Bank, Associate Data Quality Analyst at CHIA

These days, virtually all companies recognize the importance of data; it’s a question of how ready they are to invest in it with positions like data quality analyst.

Some “newcomer” industries include entertainment (especially streaming services, which live and die by subscriber engagement data), manufacturing, and food—particularly as investment in smart and AI-driven products picks up.

Data quality job posting examples: Data Quality Analyst at General Mills, Data Quality Analyst at Ford, Data Quality Analyst, Data Governance at Disney Streaming Services, Data Quality Lead at Apple

When looking at roles, take into account what kind of overall intensity you want, which is influenced both by industry and by company size. Consider whether you thrive under pressure, or if you do your best work when you have some room to breathe.

Future Outlook

The data quality field is only going to grow. The market's growth over the next few years is projected to be 17.4%1 annually, reaching a global market size of $8.47 billion.2

As part of that, there'll be increasing demand for data quality analysts.

As technology, AI, and automation get better and smarter at handling some of the more basic tasks that currently fall to data quality analysts, the role will start to focus on those higher-level parts that need human judgement, business knowledge, and input from different parts of the organization.

Given these factors, a data analyst role will put you in a strong position for finding continued work as long as you stay flexible and continue to grow your skills. Particularly, focus on growing your skills around understanding the business in context of the world at large, making complex decisions, and building relationships—things that can’t be easily automated away.

1 https://www.researchandmarkets.com/reports/4804565/data-quality-tools-global-market-trajectory-and
2 https://www.researchandmarkets.com/reports/4804565/data-quality-tools-global-market-trajectory-and