The question of finding a job is always relevant among students. Some of them even manage to gain experience in companies while studying. In this post, we will discuss why the profession of Big Data analyst is so relevant and how to create a CV for this position properly.
Big Data Analyst: The Most Wanted Job of the Future
A Big Data analyst is a precious person in the IT infrastructure. His or her responsibilities include scaling the architecture to handle big data. In addition, a Big Data analyst is engaged in data study, searching for patterns and connections in the data to create solutions based on it, which help businesses to achieve goals.
You can conditionally call a Big Data analyst an offshoot of the data scientist since the main emphasis remains on big data. The analyst is responsible for visualizing this data, developing a machine learning model, and formulating hypotheses for the business.
The high demand for this profession is because the amount of data is only increasing; there is no downward trend. As a result, large, medium, and small businesses face the need to interact with data in one way or another.
Big Data, for example, allows you to analyse your audience and identify the most relevant topics or products that will be popular during a specific time. Then, you can build both a marketing campaign and a completely new product based on this information.
Another example of Big Data analysis is when a bank checks your credit history to decide whether or not to issue a loan. Big Data analysis benefits everyone, businesses and customers alike.
Big Data analyst salaries can fluctuate greatly depending on the skills of the candidate, as well as the effectiveness of their CV and job interview. So don’t miss out on tips on how best to craft a Big Data analyst CV.
Essential Skills for Big Data Analyst
- Python programming
- Knowledge of SQL to make database queries
- NoSQL to have access to the most popular big data collection methods
- Hadoop and Spark frameworks
- Machine Learning
Of course, this is not a complete list of necessary skills. You can always add to and expand your knowledge and expertise. The essence of the Big Data Analyst profession is collecting data and finding valuable ways to apply that data to specific situations and business issues.
How to Stand Out Big Data Analyst CV Advantageously Among Competition
Sometimes the candidate is trying hard to describe his/her experience in detail but doesn’t receive job offers. Indeed, company recruiters may see the effectiveness of a CV in a completely different way. So stick to the main rules when writing a CV.
Be clear about the position for which you are applying
The first rule of an effective CV is no one-size-fits-all resume. For example, you can’t send the same CV for a data analyst and copywriter position. Instead, review your skills and experience, and describe your qualifications as required. The recruiter will not decide whether you are a good fit and certainly will not talk you down if you are not. For a particular job, you need to put together a suitable CV.
Keep your CV short
A resume shouldn’t be more than one and a half to two pages long. A recruiter spends about seven to eight seconds on the first CV screening. During that time, the eye can only catch the critical elements of the candidate’s suitability for the position.
Craft an accurate CV
A big data analyst CV should not describe your experience as a babysitter when you were sixteen. Specify only relevant experience if any and on-point skills you possess. Sometimes, for a good reason, the candidate tries to describe his or her experience as much as possible to appear a little more professional than others. To do this, the candidate may use florid language, complex sentence structures, etc. However, this does not make him more competent than others but instead creates the image of a person who likes to complicate his tasks.
Write an understandable CV
A CV should be understandable to more than just the candidate. Don’t use acronyms for names. The recruiter should be able to trace your previous experience easily. Try to stick to a timeline and logical framework when writing your CV.
Verbs set the dynamic of a resume. If you want to describe your previous experience, use verbs to describe what you did, what you were responsible for, what blocks your work consisted of. Don’t use general, lengthy language.
If a company is looking for a big data analyst, the recruiter will have a future job description describing the specific skills or experience they will be looking for. Unfortunately, there are situations where the candidate doesn’t list his or her experience, believing the recruiter can count the years on his or her own. Or the candidate doesn’t list skills, thinking they are apparent if based on experience. It is fundamentally wrong. The recruiter will not further specify all the competencies; most likely, he or she will simply sort such a CV into unsuitable. Instead, use keywords: big data, data analysis, machine learning, SQL, NoSQL, business solutions, etc., that are relevant to the position, preferably using the same language as the vacancy.
Use a summary
The last section of the CV usually consists of a “summary” section. More often than not, candidates write general phrases in this section, like “productive,” “proactive,” “team player.” The marketplace is saturated with descriptions of this kind. Use this section to reiterate what individual value you can bring to the company or team.