Data Analyst, Data Scientist and Data Engineer: The sexiest jobs of 21st century.
Why these are known as the sexiest jobs? Because the unknown can be very sexy. “Data science or Data analytics or Data engineer? Ohhhh, mysterious. That’s hot.” Then the unknown becomes known, and you wonder how you ever thought hardcore statistics looked so sexy in a swimsuit.
Okay, jokes apart, I think the “sexy” came from the following:
- These jobs can pay very well, and we all know money can be sexy.
- And also they work in some very cool spaces on very cool tech. Sexy? You bet.
- Data Science, Data analytics and Data engineer are “hot” right now, and hot is not too far off from sexy.
You may have heard the terms “data analytics” , “data science” and “data engineer” mentioned before. If you are new to the world of data, you might be wondering what these terms mean — and if you’re interested in a career in data, which is the right path for you?
So lets have a brief knowledge about these terms:
Data Analyst:
A data analyst is the one that gathers, investigates and represents data in a way so that everyone can understand it. The Data that is gathered by Data Analysts usually comes from a single source. They are responsible for cleaning, Organizing and translating raw data into actionable business insights, which are further used by the organization to make data driven decisions. Data visualization is a vital part of their professional day to day routine.
Key Responsibilities:
The responsibilities of a data analyst typically include the following:
- Designing and maintaining data systems and databases; this includes fixing coding errors and other data-related problems.
- Mining data from primary and secondary sources.
- Cleaning and dividing data to get rid of irrelevant or not required information.
- Using statistical tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts.
- Identifying new opportunities for process improvement.
- Collaborating with programmers, engineers, and organizational leaders to identify opportunities for process improvements, recommend system modifications, and develop policies for data governance.
- Designing, creating and maintaining databases and data systems.
- Fixing code problems and data-related issues.
Technical Skills:
Each year, there is more demand for data analysts than there are people with the right skill set to fill those roles.
But what skills are the most in-demand in the world of data? Let’s take a closer look at what they are.
- SQL (Structured Query Language)
- Spreadsheet
- Python/R programming
- Data Preparation
- Data Visualization (Tableau or Power BI or Excel)
- Statistics
- Data Warehousing
- Domain Knowledge
- Communication Skills
What degree do you need to be a data analyst?
- Data Science
- Computer Science
- Applied Mathematics or Statistics
- Finance/Economics
- Management Information Systems(MIS)
Average Salary:
According to some researches the “average salary for a data analyst is $70,000 per year.” There are some factors that affect the salary, including educational level, years of experience, certifications, and involvement in professional organizations. Most people move on to other jobs, such as data engineers, data architects, or data scientists once they have more than 10 years of experience in this career.
Data Scientist:
A Data scientists manage the entire data lifecycle, from collection and organization to analysis and interpretation. Their insights are usually forward-looking. This means they assess relevant historical data and extract insights that can be used as a basis to derive potential changes in consumer behavior or trends. This allows organizations to come up with long-term strategies that meet such projections.
Key Responsibilities:
Some of the primary key responsibilities of a data scientist are listed below:
- Collecting a large raw data from various sources.
- Process and clean the data.
- Integrating and storing data.
- Creating visualizations for stakeholders to understand data better
- Choose one or more potential models and algorithms and apply data science techniques, such as machine learning, statistical modeling, and artificial intelligence.
- Extending the company’s data with third party sources of information when needed.
- Enhancing data collection procedures for building analytic systems.
Technical Skills:
To become an expert in the domain, you need to master the skills required for Data Scientist positions in various companies and organizations. So, let’s take a look at the must-have skills for Data Scientist jobs.
- Fundamentals
- Statistics
- Data Preparation
- Data Visualization
- Data Integration
- Programming Knowledge
- Machine Learning
- Deep Learning
- Data Science Tools
- Big Data
What degree do you need to be a Data Scientist?
Data science has a broad scope and is inherently cross-disciplinary. Because of this, many educations are relevant. People with all kinds of educational backgrounds become data scientist. Some of them are:
- Statistics
- Computer Science
- Mathematics
- Economics/Finance
- Industrial Engineering
- MBA
- Operations Research
Average Salary:
Data scientists earn an average annual salary between $105,750 and $180,250 per year. However, compensation can vary depending on location, certifications and work experience.
Data Engineer:
While data science and data scientists in particular are concerned with exploring data, finding insights in it, and building machine learning algorithms, data engineering cares about making these algorithms work on a production infrastructure and creating data pipelines in general. So, a Data engineer is an engineering role within a data science team or any data related project that requires creating and managing technological infrastructure of a data platform.
Key Responsibilities:
Here is the list of roles and responsibilities, Data Engineers are expected to perform:
- Analyze and organize raw data
- Build data systems and pipelines
- Estimate business needs and objectives
- Conduct complex data analysis and report on results
- Prepare data for prescriptive and predictive modeling
- Build algorithms and prototypes
- Combine raw information from different sources
- Explore ways to enhance data quality and reliability
- Identify opportunities for data acquisition
- Develop analytical tools and programs
- Collaborate with data scientists and architects on several projects
Technical Skills:
Here is the list of some essential Data engineer Skills:
- Data Preparation
- Data Mining
- Data visualization
- SQL ( Structured Query Language)
- Programming Language ( JAVA or Python)
- Numerical and Analytical skills
- Data warehousing and ETL tools
- Machine learning
- UNIX, Linux, and Solaris
- Domain Knowledge
What degree do you need to be a Data engineer?
In the past few years, the demand for data engineer roles has risen astronomically. Organizations are actively looking for data engineers to address their data woes. This skillset is high in demand, and it is far from being oversaturated like other fields. So some essential degree you need are:
- Computer Science
- Mathematics
- Statistics
- Big Data
- Data Science
- Machine Learning Engineer
Average Salary:
According to some researches, “A Data Engineer earns an average salary of $90,000 per year.” Experience has a positive effect on salary, with many data engineers staying in the field for 20 years or more. The highest-paid data engineers employ their skills in programs such as Scala, Apache Spark, Java, and in data modeling and warehousing.
Conclusion:
I hope you enjoyed reading about the differences between a Data Analyst, a Data Scientist, and a Data Engineer. Let me know in the comments below which type of position you would like to pursue the most!
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