We recently carried out a survey of employers who are recruiting for data quality analyst or information quality analyst roles.

The following article provides an interesting insight into some of the essential skills your CV might just need to win those rare data quality jobs.

Creating a competitive edge when applying for data quality jobs

Before we get into the research findings let’s look at some of the basics of applying for data quality positions.

There simply are not that many jobs around for data quality professionals compared to other industries so it pays to gain the best possible advantage.

Tailor your CV to the job in hand

Whenever you’re putting forward your CV to a prospective client or employer I always find it helps to tailor your experience directly to the role required.

But we’re not talking about doctoring or fabricating information here, far from it.

What you’re doing is making it easy for the person reviewing your CV to instantly connect your skills to the role they need you to perform.

So, regardless of what skills we list in the following research, you still need to dig deep and find out what the client or employer are looking for based on discussions with the agent, HR or sponsor.

Agencies need educating and supporting to present you in the best light

Most agents are, to be frank, somewhat ill-informed with regard to data quality resourcing, experienced data quality recruiters are a very rare breed in my experience.

By taking the time to really understand the role and even talk to the employer before submitting your CV you should stand a better chance of getting into the interview phase.

Then you need to tailor your resume precisely to those needs.

Sounds like common sense? Maybe but then why do some many ignore such obvious advice?

So lesson one is to take that extra half hour to completely match your experience to what the employer needs.

Create short, focused CV's that make you stand-out

I’ve lost track of how many CV’s I’ve read which drag on for page after page listing 3 month stints on completely irrelevant projects when what I was looking for was a standout data quality analyst. 

Essential data quality skills – the findings

Before we begin, let’s briefly explain how we carried out the research and you can do the same quite easily.

Over a 2 month period we scanned job listing websites (like Jobserve.com) for data quality analyst related roles and recorded the postings.

We then went through each listing picking out the key skills or experience the employer demanded.

This culminated in a simple spreadsheet which showed a large number of categories so this was then refined into an aggregated listing with further sub-categories.

Data Quality Analyst Skills by Occurrence

Data Quality Tools are now the most common requirement employers are searching for

What the image above clearly shows is that when employers are looking for data quality analysts they are expecting skills in data quality products.

Now, taking a purist approach, data profiling and data discovery don't necessarily require data quality tools to complete but in terms of employer thinking we can assume that this category also equates to data quality tool experience. This takes the overall figure for data quality tool requirements even higher.

What this invariably means is that if you lack skills in a well known data quality tool you may struggle to find suitable data quality analyst roles.

Our research indicated that Ab Initio, Ascential (IBM), Business Objects, Trillium, Datanomic, FirstLogic (Business Objects), IBM, Informatica and SAS are the main tool vendors the employers were searching for.

This is confirmed by data quality recruitment specialist, Vivamex:

As data quality becomes more mainstream customer requirements will become more specific. They will look for skills in specific tools by name, and eventually as maturity continues apace even specific versions.
Our advice to a technically based data quality analyst is to obtain broad based experience and then concentrate on one of the perceived front running vendors so that they can be perceived as "really solid" in that toolset.

Experts who are stood a step back back from the tool itself such as analysts, architects and project managers can retain a little more flexibility.

Latterly when cost becomes a significant factor, many practioners will move towards these business facing roles or move away from data quality completely as the overseas competitors move in, "production line" methods appear and salaries or rates degrade.

This is a time of expansion and possibilities however. It is a good juncture at which to become involved in data quality.

Excellent KPI and reporting skills are key essentials

KPI and reporting come next and that is no real surprise but it clearly demonstrates the need for good analysis and reporting skills with the ability to convert the impact of the data quality defects into a language the business can digest and act upon.

Can you communicate and engage with the business effectively?

Employers are clearly looking for people who can interact effectively with the business and technical community as some form of communication and business engagement appeared in most of the roles.

There is a strong emphasis on business requirements capture, stakeholder management and dealing effectively with 3rd party suppliers in many of the roles so this needs to come across well in your background and interview.

Metadata - understand, manage and deliver

Companies are looking for strong metadata management skills so ensure that you have this highlighed in your CV. Get experience of creating and deploying metadata repositories.

Tip: If you don't have a metadata repository in your project why not follow this tutorial and create your own:
How to create a data quality management repository in less than an hour...

Do you have experience of creating data quality standards, policies and frameworks?

If so ensure this comes out loud and clear because employers are looking for practical experience at either creating, supporting or delivering these vital data quality components.

Tip:We will shortly be posting an article on how one of our members created a data quality framework and will be including the data quality framework in the article so subscribe to our RSS feed to stay posted:
http://www.dataqualitypro.com/data-quality-home/rss.xml

Are you an SQL guru?

If you are that's still a big benefit as many employers were looking for very advanced SQL, MySQL v5 was mentioned several times but SQL experience from any platform is always looked upon favourably in my experience.

And on a final note - the confusing role of the Data Steward

There is often a certain amount of confusion I feel over what duties a data steward must perform and judging from the job postings most employers also have a difference in opinion.

The verdict?

Employers appear to view data stewards basically as basic administration staff or data quality analysts.

On the whole the skills they presented for data stewards matched exactly with those of data quality analysts.

There are also very, very few jobs with this title so if you're looking for a career as a data steward I would certainly look to build a broad set of skills to take on alternative roles when employment conditions dictate.

Plugging the gaps

If you scan through the remaining categories you should be able to get a feel for what employers frequently look for and assess where your CV and skillset needs to improve.

But don't take our word for it, scan the job postings and set up daily downloads searching for the roles you are interested in to create your own research.

• Check the frequency - are there regular jobs posted for your role?
• Is this a niche that is growing or extending into new areas?
• What are the hot skills or tools that most employers are looking for?
• Do you have departments or teams that use these products?
• Will they let you get onboard either in a project or your spare time to upskill and extend your CV?

It is important to continuously monitor what employers are really searching for and not some idealised industry perception of what a data quality analyst or data steward should perform.

After all, it's the employer who pays your wages, not industry opinion, so always match your skills to what employers really need.

What do you think? Do you agree? Do these skills seem far too technical? Should there be more clearly defined roles across the industry? Are employers relying far too much on data quality technology?

Please respond with your thoughts and opinions below...