The fields of data science and data technology are growing rapidly. According to McKinsey Global Institute, the shortage of qualified and experienced experts in these areas could face a shortfall of 140,000 to 190,000 people by 2018; demand for talent is more than double the numbers of available candidates. Data scientists, experts in such platforms as Hadoop and Spark, and IT managers who possess the ability to thrive in dynamic, data-driven cultures will all be in enviable positions regarding their employment opportunities.
Enterprises in a diverse range of industries find that they need Big Data talent as competition drives the growth of data platforms, which intern confers financial advantages to those that have the resources to automate processes and pull insights out of the information flows that support their operations. Recruiting data scientists who have the right mix of quantitative analysis, business, and engineering skills is becoming an urgent priority for companies that wish to lead their fields. There are not many competent candidates who are unemployed, seeking a possible career move; you will have to go hunting and find them through aggressive recruiting activities.
So, What Does Big Data Talent Earn?
According to Glassdoor.com, Data Scientists earned salaries on the average of $113,436 in mid-2016, equivalent to $54.54 based on a 40-hour workweek. However, there is a significant amount of variation in salaries; leading-edge technology companies offer higher salaries while those that are perhaps, more traditional and less data-centric, pay significantly less well. The spread in Big Data salaries may tighten up, and the average increase, as recruiters attempt to entice skilled workers with better packages as demand churns the market.
Big Data Hourly Earnings By Occupation (source: Glassdoor)
| Occupation | Average hourly rate, $ |
|---|---|
| Data scientist | 54,54 |
| Database Admin (Hadoop qualified) | 52,88 |
| Quantitative Analyst | 52,02 |
| Data Engineer | 45,93 |
| Database Admin (entry level) | 32,92 |
Based on these figures, IT pros with knowledge and experience in Big Data can expect to earn $55 to $55 per hour in the current hiring market. Additionally, according to bigdatarecruiter.com, Data Analytics Managers can make between $43 and $85 per hour, depending on the number of direct reports they supervise.
Big Data Earnings Range By Occupation (source: BigDataRecruiter)
| Occupation | Annual range, $ |
|---|---|
| Data analyst (entry-level) | 50,000 - 75,000 |
| Data analyst (experienced) | 65,000 - 110,000 |
| Data scientist | 85,000 - 170,000 |
| Analytics manager (1-3 direct reports) | 90,000 - 140,000 |
| Analytics manager (4-9 direct reports) | 130,000 - 175,000 |
| Analytics manager (10+ direct reports) | 160,000 - 240,000 |
| Data engineer (junior / generalist) | 70,000 - 115,000 |
| Data engineer (domain expert) | 100,000 - 165,000 |
Hiring Data Science Job Candidates
There is a limit to motivation employees to jump ship with higher pay; other, less tangible factors such as workplace culture may play a part in decisions to leave an employer at the professional level. However, with rapid turn-over and intense competition for talent, it is salaries and benefits that have the most easily accessible appeal for growing companies.
Hiring managers and recruiters under pressure to attract data scientist will have to be aggressive and clear on the proposition that they can deliver for suitable candidates. Higher pay, generous benefits, and the opportunity to be part of the action in a glamorous industry will continue to be the norm. With no sign of demand letting up it is likely that data scientists and related careers will see further salary growth; a situation that will enable top talent to dictate the terms of their choosing.
Local recruiting and IT staffing agencies normally charge a recruiting fee on top of each Big Data candidate placement. The majority of recruiting fees run between 15% and 25% of the candidate’s total first year annual earnings. As such, you should anticipate to pay a way more for your Big Data talent. Also take into consideration idle time (i.e. time needed to hire and onboard your data specialist or set up an entire team of data scientists and engineers) that'll cost you an overhead, too! Eventually, Big Data talent will cost you a fortune and there's no guarantee you'll be able to derive the right value from your project. (Read about 8 mistakes most IT managers make with their data analytics).
Is there an alternative to unaffordable recruitment fees?
There is one indeed - re-invented IT staffing! In order to lead the way as far as Data Analytics, you need to pay attention to the following three factors prior to engaging with an IT staffing agency:
- Agency's ability to provide a comprehensive consultancy and help build your own Big Data roadmap that is based on your particular issues and how Big Data initiatives are going to help resolve them, as well as on your ROI / value expectations.
- Agency's ability to look beyond the national Big Data talent pool in order to help you:
- Shorten your time to hire and time to market accordingly,
- Reduce your hiring costs,
- Deliver competent and experienced talent from abroad, as the same-level local talent can be truly unaffordable (that's why many companies in the United States can only afford junior or mid-level talent that makes little sense for their Big Data project success!)
- Innovative pricing model (i.e. monthly Salary + Fixed Fee instead of recruitment service fees).
