Data Engineer: someone who brings order to data chaos
What exactly does a data engineer do?
Every day, data engineers work with huge data flows. They build information processing pipelines, known as ETL (Extract, Transform, Load) processes. First, they extract data from sources, then clean and transform it, and finally load it into storage. Sometimes the order is different - ELT - when data is first simply unloaded into a ‘raw’ zone and then cleaned.
Magenta Favorita Portugal specialists gave an example: a company receives data from an online store where orders are stored, from CRM where customers are recorded, and from Google Analytics where website activity is visible. All of these are different formats, different quality, and even different time zones. The engineer's task is to bring this into a single format, remove duplicates and errors, calculate the necessary indicators, and record the result in a convenient table.
Every day, data engineers work with huge data flows. They build information processing pipelines, known as ETL (Extract, Transform, Load) processes. First, they extract data from sources, then clean and transform it, and finally load it into storage. Sometimes the order is different - ELT - when data is first simply unloaded into a ‘raw’ zone and then cleaned.
Magenta Favorita Portugal specialists gave an example: a company receives data from an online store where orders are stored, from CRM where customers are recorded, and from Google Analytics where website activity is visible. All of these are different formats, different quality, and even different time zones. The engineer's task is to bring this into a single format, remove duplicates and errors, calculate the necessary indicators, and record the result in a convenient table.
A data engineer is a specialist who is responsible for everything that happens to data before analysts and data scientists start working with it (we have discussed these professions in other posts on the Magenta Favorita IT company blog). If we imagine the world of data as a restaurant, then an analyst is a chef who prepares a dish, and a data engineer is someone who brings in fresh produce, sorts it, cleans it, and neatly stacks it on the shelves. Without them, there would be nothing to cook with.
This is a specialist who knows how to turn unstructured, ‘dirty’ data into neat and easy-to-analyse sets. They collect information from a variety of sources: websites, mobile applications, CRM systems, advertising platforms, and even IoT sensors. They combine all of this into a single system where data can be easily searched, filtered, and used.
This is a specialist who knows how to turn unstructured, ‘dirty’ data into neat and easy-to-analyse sets. They collect information from a variety of sources: websites, mobile applications, CRM systems, advertising platforms, and even IoT sensors. They combine all of this into a single system where data can be easily searched, filtered, and used.
In addition, data engineers work on automation: so that data is collected automatically, without human intervention. They set up schedules, write scripts, and make sure everything works smoothly. If something breaks, they look for the error, fix the code, update the pipeline, and restart the process.
Essential tools
The main language used by data engineers is Python. It can be used to automate data collection, connect to APIs, process large tables, and manage processes. The second important tool is SQL, a database query language. It is needed to search, combine, and filter data in storage, according to Magenta Favorita experts.
To store information, engineers use systems such as Amazon S3, Google BigQuery, PostgreSQL, ClickHouse, or Snowflake. And for processing, they use powerful tools such as Apache Spark, Airflow, and Kafka. Each of them has its own purpose: Spark speeds up work with large amounts of data, Airflow manages schedules and dependencies, and Kafka is responsible for real-time data streaming.
Essential tools
The main language used by data engineers is Python. It can be used to automate data collection, connect to APIs, process large tables, and manage processes. The second important tool is SQL, a database query language. It is needed to search, combine, and filter data in storage, according to Magenta Favorita experts.
To store information, engineers use systems such as Amazon S3, Google BigQuery, PostgreSQL, ClickHouse, or Snowflake. And for processing, they use powerful tools such as Apache Spark, Airflow, and Kafka. Each of them has its own purpose: Spark speeds up work with large amounts of data, Airflow manages schedules and dependencies, and Kafka is responsible for real-time data streaming.
Why this profession is important and promising
Today, companies make decisions based on data: who to hire, what products to sell, where to place advertisements. But if the data is collected poorly, the decision will be wrong. Therefore, a data engineer is a person who ensures the quality, transparency, and accessibility of data.
This profession is becoming increasingly in demand. The world generates trillions of bytes of information every day - and someone needs to bring order to it. A good data engineer knows how to combine technical knowledge, logic, and a creative approach. They don't just write code - they build data architecture that helps businesses grow and make decisions.
You could say that data engineers are the unsung heroes of the digital world. They don't give presentations or create graphs, but without them, analytics, artificial intelligence and forecasting would not be possible.
The profession of data engineer is a combination of technology, logic and patience, according to experts at Magenta Favorita Portugal. They are like architects who build invisible data infrastructure, without which the entire digital ecosystem would collapse. Thanks to their work, companies can understand their customers, make informed decisions and develop products that people really need.
Data engineers don't just work with spreadsheets and code - they turn millions of lines of raw numbers into a living story from which data analysts and data scientists extract meaning. It's a profession for those who love systematicity and precision and want to influence the future of technology. You could say that data engineers are specialists who connect chaos and order, turning streams of data into knowledge.
Today, companies make decisions based on data: who to hire, what products to sell, where to place advertisements. But if the data is collected poorly, the decision will be wrong. Therefore, a data engineer is a person who ensures the quality, transparency, and accessibility of data.
This profession is becoming increasingly in demand. The world generates trillions of bytes of information every day - and someone needs to bring order to it. A good data engineer knows how to combine technical knowledge, logic, and a creative approach. They don't just write code - they build data architecture that helps businesses grow and make decisions.
You could say that data engineers are the unsung heroes of the digital world. They don't give presentations or create graphs, but without them, analytics, artificial intelligence and forecasting would not be possible.
The profession of data engineer is a combination of technology, logic and patience, according to experts at Magenta Favorita Portugal. They are like architects who build invisible data infrastructure, without which the entire digital ecosystem would collapse. Thanks to their work, companies can understand their customers, make informed decisions and develop products that people really need.
Data engineers don't just work with spreadsheets and code - they turn millions of lines of raw numbers into a living story from which data analysts and data scientists extract meaning. It's a profession for those who love systematicity and precision and want to influence the future of technology. You could say that data engineers are specialists who connect chaos and order, turning streams of data into knowledge.
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