As a recruiter who works with many different clients, the term “big data” is heard a lot. It seems like every company is searching for game-changing big data hires, whether it is an entry level role or a senior level spot. But what does big data actually mean, and how can we, as recruiters, make sure we are effectively fulfilling big data roles for our clients?
Big data is defined as large data sets that are analyzed to find patterns and trends to help a company grow and learn more about their clients’ and/or customers’ behaviors. That being said, every company has their own analytical needs depending on their value proposition and their target markets. Here are some tips I have learned to better understand my clients’ needs:
Define Client Goals
Companies have different approaches when it comes to big data. Make sure as a recruiter you understand what exactly it is the client is looking to do with the information they collect. What are their goals? Are they looking for someone to create algorithms to analyze the numbers using R, or are they looking for someone to process the data using Hadoop clusters? Some companies want to assess in real-time and some want to store their intelligence and analyze it the next day. How your client wants to process information can determine what experience your targeted candidates need.
Know Required Tech
Research the tools and technologies your client requires. You do not have to be an expert, but you should understand what these programs do and how they work together. There are many different technologies used to quantify and qualify and it is your job to find valuable candidates who excel with these platforms. Understanding the necessary tools that these roles utilize helps you to better refine your search. Here, your big data hiring protocol becomes clearly-defined, understood, and manageable.
Research Like a Detective
Look carefully at LinkedIn profiles and any other potential profiles you notice. Sometimes it is not always clear what a person’s foundation is. Their profiles could say they know Hadoop or have worked with data warehouses. However, he/she may not be a data architect, and depending on the level or responsibilities of the role, he/she may or may not be the best fit. Many companies use the same title for roles that are not similar at all, so it is imperative to examine candidate profiles with a fine-tooth comb.
Big data talent searches sound like big problems for recruiters. Don’t panic when you're recruiting and hiring! Keep your clients’ goals and objectives at the forefront. Are they looking for someone who has experience with specific types of data (i.e. ecommerce or banking)? Understand what your client is trying to accomplish. Research the vital software packages your prospects need to know. Thoroughly research every lead you encounter. Don’t be fooled by titles. Investigate backgrounds, skillsets, and capabilities. Ultimately, your data analysis impacts your client's.
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