Why are over 800,000 Data Jobs Always Open?

I could answer the question, "Why are 800,00 Data Jobs Always Open," with one sentence. MOST, not all, of the resources conducting the hiring are using outdated processes designed for manufacturing and know next to nothing or absolutely nothing about the advanced data fields for which they are trying to hire. Also, nobody wants to hire someone better than they are for their own job security. Anyone who is good with data will probably be elite. However, that's okay. Hiring managers simply have to see evidence of the employees talent, such as articles, and tangible work produced in the past, and see their skill as an asset instead of a threat. Without competent resources, most teams will fail anyway. There is actually far more job security if one can show consistent success.

Every week I get approximately 63 calls about data related jobs, but not one of the companies has had a practical exercise or an expert in the field on the line to validate my skills from a practical exercise. In 29 years, only one company has said, "Create a conceptual, logical, and physical data model from these five business requirements, and send us a UML diagram for validation." That's the only way to know for sure that the person can actually do the job. Whether it be data modeling or modeling and data governance, the resource must be able to interpret business requirements, then transform them into a valid data model with data governance rules encoded into the structure. Companies should have practical exercises for each job for which they need resources or be able to see their work on an online profile site such as LinkedIn.

Information Technology professionals cannot be hired based on educational credentials and references because universities are more than thirty years behind in technology training and even when they do train students for technology, it's designed for MANUFACTURING!!!!!! Even then, the knowledge is just surface knowledge with near zero experience and depth. Although the US has not been a primarily manufacturing economy for decades, nearly one hundred percent of managers and business degree students are trained for MANUFACTURING!!!!!. Information Technology (IT) is not manufacturing. Universities are so far behind, thirteen universities have tried to hire me to teach data governance and data modeling in just the last three years.

Additionally, companies are trying to cut costs by grouping twelve jobs into one job description. It is common for me, a data modeling and data governance specialist, to get calls and interviews that focus solely on Python, which has NOTHING to do with data modeling nor data governance, hadoop, which does not even support data modeling, and dozens of other obsolete technologies that have nothing to do with my core skill set. YOU CAN'T FIND ANYONE BECAUSE YOUR JOB DESCRIPTION IS FOR 12 JOBS!!!!! Corporate attempts at SLAVERY through free overtime and low wages is the primary obstacle for finding and hiring the right people.

The result is that companies are now spending a combined three TRILLION DOLLARS / YEAR ON BAD DATA ISSUES BECAUSE THERE ARE OVER 800,000 UNFILLED DATA RELATED POSITIONS AND OVER 1 MILLION FILLED WITH INCOMPETENT PEOPLE. Companies have become so greedy, they are cutting the cost cutting measures. Information Technology itself is a cost cutting measure. So, any manager with logic should be able to see that cutting costs in IT will increase costs everywhere else! Most companies are losing up to 33 percent of their annual revenue to bad data issues and data related fraud just to reduce the salaries of their IT professionals and contractors.

I once invoiced a major bank one million dollars to fix an issue with a data model in Oracle that was costing the bank over 2 million dollars / year in court fines because they could not deliver data when it was requested via subpoena. The same bank was losing over 20 million / year due to inefficiencies in in their data systems and suspected that there were more loses due to licensing over 200 database instances that I could have condensed into one database system on two data appliances. The licensing alone was an additional 30 million dollars / year. What did the bank say to my proposal? "We're not paying you a million dollars just to fix a data model with some minor architecture re-design." What did I say? "This is not minor. It's way bigger than you think. Let me know when you get tired of losing 52 million / year and I'll come back and fix it." What did they do? They paid IBM almost one billion dollars, a few years ago, to fix their issues. IBM failed miserably by trying to outsource the job to India. The same bank called me back two weeks ago, but still would not pay my invoice of one million dollars. One of their top executives literally said, "He's better than IBM," in reference to my previous work with Business Intelligence, but they still could not bring themselves to pay for my labor. And they still have not paid the bill for the BI work. I throw up my hands...

The image below shows the usual over 800,000 jobs available with over 200,000 matches to my profile based on pure skills matches. However, since nearly everyone who recruits and interviews for jobs have no idea what any of the 56 skills I have mean or do, it's very unlikely that I will be able to work for most of the companies. Additionally, nobody wants to pay living wages for high quality work.

For example, recently someone from Toyota asked me if I had a degree related to Data Modeling without checking if such a degree exists. It does not exist. Data modeling surface knowledge is taught for 1.5 hours at MIT for computer science students, but that's it. It usually takes ten to fifteen YEARS to master data modeling. Since that is beyond the scope of any university program, no university attempts to train students in a pure data field. The only way to learn data modeling and real-world data governance is from on the job training, which also no longer exists, and long-term experience.

My analysis of Toyota indicates that they are having current and long-term issues with their cars due to parts being imported from other manufacturers such as BMW. Over time, the one reason people buy Toyotas, reliability, will be gone and Toyota will lose market share drastically, which will cost billions. They need an automated supply chain and quality assurance system with automated incident analysis for parts failures. Additionally a customer demographics system would help their sales, especially in the conversion from the used car market to the new car market.