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Data Engineer

By Cecilia Caselli
Published in Fundamentals
November 03, 2023
1 min read
Data Engineer

Data Engineer

As of today, almost every industry collects massive amounts of data to make business—oriented decisions. We have indeed already mentioned the importance of data scientists and analysts when it comes to making intelligent decisions. In this regard, data engineers work to make data accessible for data scientists to use it.

Data engineers are responsible for building systems for collecting, transforming, and storing data. They create pipelines to convert raw data into usable formats for other data collectors to interpret it.

Your tasks include:

  • Building and maintaining data infrastructure for an optimal ETL (extraction, transformation, load);

  • Ensuring data accessibility at any time;

  • Comply with company data policies and assure data privacy and confidentiality;

  • Improving data systems reliability, speed, and performance;

  • Building pipelines, data warehouses, and reporting systems.

At the same time, to make data accessible to other data collectors they are:

  • Cleaning and wrangling data into usable formats;

  • Developing data tools and APIs for data analysis;

  • Building algorithms and statistical methods to interpret data;

  • Cooperating with other team members, managers, and stakeholders to address the company business goals.

As for your skills-set, you know:

  • Programming languages. SQL, NoSQL, Python, Java, R, Scala;

  • Relational and non-relational databases. They are needed for storing data;

  • ETL (extract, transform, load) systems. Common ETL tools are Xplenty, Stitch, Alooma, Talend.

  • Data Storage. Depending on the type of data, they may be required to be stored in different ways.

  • Cloud computing;

  • Big data tools, like: MongoDB, Hadoop, Kafka.

  • Data security. To protect data from any sort of potential stealth or loss.

What’s the difference between a Data engineer and Data Scientist? Imagine we are at a restaurant, the chef - represented by the data engineer - does all the steps needed to make the dish ready for the server - represented by the data scientist - to bring to the diner.

However, there is a better way to explain it:

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Cecilia Caselli

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