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DataOps Engineer: Complete job description

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For companies wishing to remain competitive, effective data management is imperative. Today, many organizations are looking for people capable of mastering these data management, processing and optimization techniques. In other words, these organizations are looking for Dataops engineers.

In this article, find out everything you need to know about becoming a Dataops engineer: training, assignments, jobs, salary, etc.

What is Dataops?

In recent years, two innovations have shaken up the business world: Data Science and the DevOps methodology. The result is DataOps, an agile methodology designed for data analysis.

The aim of DataOps is to simplify the design, development and maintenance of data analysis applications. The aim is to improve the way data is managed and products created.

What is the role of a DataOps engineer?

The DataOps engineer is an essential link in data processing teams. A DataOps engineer is the bridge between development teams, data scientists and operational teams within an organization. Their main role is to guarantee the availability, quality and reliability of data throughout its lifecycle. This involves implementing practices and tools to effectively manage data pipelines, from collection to final analysis.

What are the missions of a DataOps engineer?

DataOps engineers are responsible for data development, and create the tools that data engineers and analysts will use during development. They don’t work directly with the data, but intervene in the environment and processes by which other team members can create data products.

The DataOps engineer is responsible for various tasks within the data environment:

  • Data Pipeline Management: DataOps engineers design, develop and maintain data pipelines. These are essential for transferring data between numerous sources, systems and applications.
  • Automation: Automation plays a central role in the work of the DataOps engineer. By automating data management processes such as extraction, transformation and loading (ETL). These professionals reduce the impact of human error and speed up the time between collection and analysis.
  • Monitoring and Problem Solving: DataOps engineers constantly monitor data pipelines for errors, bottlenecks or malfunctions. They intervene quickly to resolve problems, minimizing potential interruptions to data flows.
  • Security and Compliance: Data security is a major concern. DataOps engineers implement robust security measures to protect sensitive data, and ensure that data management practices comply with current regulations.
  • Cross-functional collaboration: DataOps engineers work closely with development teams, data scientists and other business stakeholders. This collaboration facilitates understanding of specific business needs and ensures that data pipelines meet the organization’s overall requirements.

How much does a DataOps engineer earn?

On average, an entry-level DataOps engineer earns around 35,000 euros a year. With experience, the average salary rises to 45,000 euros. In some regions and larger companies, salaries can even reach 55,000 to 60,000 euros or more for experienced DataOps engineers.

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