According to Forbes, the modern world produces approximately 2.5 quintillion bytes of data every day. The data generation has been driven by multiple factors like the growth of internet-connected devices, social media platforms, shift towards online banking & payment, mobile apps.
These data may seem useless to a normal individual, but it holds potential for modern businesses and organizations. Over the decades, the rapid growth of data has led to an explosion of demand for skilled professionals with exemplified data skills. In fact, professionals are taking training courses, like a data analyst course in Pune, to gain the right skills and become eligible for data-related jobs.
When we talk about “Data,” we all know that this field has been dominated by Data Engineers, Data Scientists, and Data Analysts, and they will continue to do so. But, in recent years, a new profession has begun to take shape, i.e., Analytics Engineer.
Let us step up and know what an analytics engineer is and how you could become one.
What is an Analytics Engineer?
An Analytics Engineer is responsible for bringing the most effective, integrated, and robust data models and products to existence. In addition, the individual can bring business awareness with technical expertise and transition in data development.
An Analytics Engineer’s role is somewhat similar to that of Data Analysts, Data Scientists, and Data Engineers. Although, these roles have their unique specialty in their own discipline with a new and evolving role.
The Analytics Engineer works to support each of these roles and empower them to make better use of the organizational data.
Roles and Responsibilities of an Analytics Engineer
As a member of the most important team of any organization, the Analytics Engineer role requires an equal amount of technical and business aspects of the organization. Some of the roles of an Analytics Engineer are:
- Collecting and integrating data from multiple sources
- Provide clean and transformed data ready for analysis
- Building data platforms to be used by other team members
- Maintaining data documentation
- Optimizing data warehouse as per requirements
- Collaborate with team members to understand and collect business requirements and design data models
- Crafting codes that meet organizations standards and database environments
- Discovering the right set of opportunities for an organization to improve its system, enterprises, and process
- Training other team members, so they are also capable of understanding and using various data tools and communicating
Tools Used by Analytics Engineer
The tools used by an Analytics Engineer depends upon organization to organization, but there are a few common tools used:
- A cloud-data warehouse for storing data – Snowflake, Redshift, Bigquery
- Data extraction and loading – Snitch, Fivetran
- Data modeling tool
- BI tool – Mode, Chartio, Looker
These tools make their job quite easy and help analysts in several ways, like:
- Complex data ingestion
- Spot an error immediately in the dashboard if something breaks in
- Build charts and reports to share with business
Analytics Engineer Salary
According to the data collected by Talent, the average salary of an Analytics Engineer is approximately $132,500 per annum.
That being said, the salary of an analyst varies from organization to organization and the location. It also depends on the skills and the experience & expertise you bring to the table.
Develop The Right Skills To Break in the Field
If you are considering a career in the data space as an Analytics Engineer, you must start developing the right skills you will need to succeed.
To become an Analytics Engineer, there are some common skills and experience that are required. So, what do the skills look like?
- SQL
- Python
- Data Visualization
- dbt
- Git
- Strong analytical skills
With these skills, one also needs to have a fair amount of work experience implementing their skills:
- 4+ years of experience in the data field
- 4+ years of experience working with a large scale Data warehouse
- 4+ years of experience of designing, implementing, and operating dimensional enterprise model
- 2+ years of experience building dashboards and reports in a data visualization tool
- 2+ years of experience in creating project plans
The unique position held by an Analytics Engineer in the data team between Data Analysts, Data Scientists, and Data Engineers, an Analytics Engineer must have multiple domain skills. Strong technical and software engineering skills will help you communicate and work with the rest of your team members.
Many engineers and Data Science enthusiasts find that they fall into the career after working in a data team for several years, upskilling themselves with different skill-sets required to excel. But a quicker and effective path to the field of data space is to earn a certification designed to prepare you for a role such as the Post Graduate Program in Data Analytics.
Not all Data Analytics programs are created equally, so for that reason, it’s important to evaluate the curriculum of your program to understand the prerequisites and outcome, whether it has been designed to help you develop specific skills.
Regardless, how you jump into this data space field, a career as an Analytics Engineer will be a rewarding one. If you are interested in data and want to pursue such a career, you should develop the skills that will help you perform your job.
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