What is analytics engineer? Meet the new profession of the data world

Analytics engineers transform data into information and visualizations that are relevant to businesses.

The data team has modernized, and with the rise of analytics engineering, it's the new profession in the data world.

In this article, we explain what an analytics engineer is, how they differ, and what their responsibilities are in modern data teams.

Enjoy and have a good read!

What does a modern data science team mean?

The cost reduction of cloud data warehouses, the evolution of business intelligence tools, and the emergence of systems for data transformation have changed the use and access of data science and analytics for companies and professionals in the field.

This implies the emergence of new responsibilities, roles, and, of course, new data professions.

Hence, the need for a new position in the world of data science arose:

Analytics engineer - Analytics engineer.

Today, without even knowing it, many data professionals (such as data analysts) already work as analytics engineers.

Do you belong to this group?

What is analytics engineer?

Analytics engineering is an area of data science focused on transforming data into information and visualizations that are relevant to businesses.

In other words, an analytics engineer is the person responsible for making all this happen in data transformation.

The main goals of an analytics engineer are:

• bringing data closer to organizations;
• Assist business end users in making decisions.

To this end, analytics engineers are at the forefront of all stages of data transformation, including:

1. Structuring transformation flows
2. Creation and application of business
rules 3. transforming data into BI visualizations and dashboards

Simplifying...

Analytics engineers organize and transform databases to make business information accessible to end users, helping them make better decisions.

As a result, by focusing on the technical side of data transformation, analytics engineers empower managers to perform robust analysis without needing technical notions or worrying about the complex part behind data analysis.

Considering the immensity of names and positions in the world of data science, you may wonder: was this position created out of mere preciousness?

No.

There's a reason for that and we'll explain it.

What has changed in the traditional data team?

Talking about the traditional data team is a fundamental subject for understanding how the career of an analytics engineer came about.

Generally, the structure of a data team follows this composition:

- Data
Engineers- Data
Analysts- Data Scientists

But this is changing due to new technologies in the field of analytics, such as:

· data warehouse technologies (Redshift, BigQuery, and Snowflake)
· data pipelines as a service companies (Stitch, Fivetran and Kondado)
· BI and SQL tools (Looker, Mode and Periscope)

As a result, the roles of data analysts and traditional data teams as a whole are being drastically altered.

How does the modern data team behave?

Responding to the changing world of data science, the modern data team is agile and able to adapt quickly to responsibilities and new tasks.

And this was further emphasized with the shift from ETL to ELT.

Don't know what we're talking about?

Replacing the process from ETL to ELT means that data in a variety of formats can now be stored in a data warehouse before it is even transformed, rather than the other way around, as is the case with ETL.

When changing the steps of the data pipeline, the modern team was faced with the following opportunity:

Explore the skills of technical data analysts with strategic business notions to model raw data into consistent information for decision makers.

And that's exactly where a super data analyst, or analytics engineer, comes into play!

What differentiates analytics engineers from other data professionals?

What is the difference between data engineers, data analysts, and analytics engineers?

We explain!

While data engineers focus on the technical side of structuring and connecting data, analytics engineers transform it into understandable information and visualizations for analysts and business end users.

What about data analysts?

Data analysts devote most of their time to analyzing data, unlike analytics engineers, who focus on a stage prior to analysis.

In other words, analytics engineers transform data into information and visualizations that are accessible, mainly through SQL, for analysts and business users.

To make it easier for you to understand the differences between these professionals, we'll use the closet analogy, created by Sara Barles, analytics engineer at Hubspot.

Understand

"Data engineers build the cabinet, they gather the wood and tools needed to assemble it. Analytical engineers, on the other hand, open the cabinet and start placing the plates, mugs, bowls to arrange it in a certain order. This can be arranged in specific colors, shapes, or sizes. Then the data analysts go into the closet and know where everything is, since it's well organized. So they can grab the little blue mug they've been looking for and make them a cup of tea! " (our translation)

What are the responsibilities and skills of an analytics engineer?

Have you noticed that the role of analytics engineer serves as a bridge between engineers and data analysts?

To do this, an analytics engineer has some specific responsibilities and skills.

Responsibilities

Considering that this analytics engineer career is still very new in the market, it is worth remembering: responsibilities can still vary from company to company.

Despite this, the main one is to create data products that answer key business questions and help stakeholders make decisions efficiently.

In addition, analytics engineers are also responsible for:

1. Provide for data transformation in the ELT
process 2. Manage data and cloud
platforms 3. Assist in data-driven discussions and decisions at the departmental
level 4. Create, monitor, establish, and forecast business and product
metrics 5. build dashboards in BI, data warehouse and ELT
6 tools. create and automate intelligent reports using tools such as Data Studio, Power BI, Tableau, etc.

Skills

Analytics engineers are technical and strategic professionals.

For example, you can identify who is an analytics engineer by the technologies they handle, such as Snowflake, BigQuery, Redshift, Stitch, and Fivetran.

Remember, however, that your notions of infrastructure, data connection, and data warehousing are basic – that part is left to data engineers.

In addition, engineers and analytical engineers are fascinated by solving business problems and helping end users extract value from data.

Therefore, the skills required to become an analytics engineer include not only technical issues, but also business issues.

They are:

· experience in querying data with SQL
· Ability to communicate with various business
areas· understanding of programming languages (e.g. Python, R etc.)
· Business
Knowledge· familiarity with BI tools such as Metabase, Looker, or Tableau
· advanced knowledge in SQL and database

What is the future of this career?

Before 2019, here in Brazil there was still little talk about analytics engineers, but that has changed.

Today, leading companies in data science and analytics, such as Nubank, Spotify and dbt, already recognize analytics engineer as a promising career.

And we at Indicium share that thought as well.

Therefore, there is quite a propensity in the industry to recognize this professional.

Despite this, there is still a long way to go to better define the responsibilities, scope, and duties of analytics engineers.

But one thing is certain: everything indicates that this trend is here to stay.

Do you want to know even more about this profession on the rise?

We are pioneers in Brazil with the Analytics Engineering Training from Indicium Academy.

A complete course for those who want to learn from our professionals to be an expert in serving the fastest growing market in the world.

To learn more, please contact us.

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