What are the roles and responsibilities of a Data Engineer

Data Science, AI and ML
1

Data engineers are typically assigned to one of three key roles:

Generalists: They are typically found in smaller teams where data engineers are expected to handle a variety of data-related tasks.

Database Centric - Found in larger teams where data flow is a big deal and data engineers have to focus more on evaluating various databases with data warehouses.

Pipeline Centric - Found in the medium business segment, where data engineers and data scientists are expected to work together to make the most of data.

Data engineer responsibilities are:

  • Optimal data pipeline architecture for data input and processing is created and maintained.

  • Assembling large, complex datasets that meet business requirements

  • Internal procedure improvements must be identified and implemented.

  • Building Infrastructure for ETL jobs from a variety of data sources.

  • To manage a variety of technical difficulties, collaborate with internal and external team members such as data architects, data scientists, and data analysts.

  • Obtaining data requirements and managing metadata.

  • Modern security mechanisms for data security and governance.

  • Hadoop, NoSQL, Amazon S3, and other technologies are used to store data.

  • Data processing using contemporary tools that aid in the management of data from a variety of sources

  • Creating models and uncovering hidden patterns in data pieces

  • Data management techniques must be integrated into the organization’s current structure.

  • Assist with the development of a robust infrastructure and seamless third-party integration.

  • Conduct research and find tasks that can be automated.

  • Learn and use a variety of scripting languages.

2

A big data engineer’s job is to create, maintain, and ensure a production-ready big data environment.

Architecture, technology standards, open-source choices, and data preparation and data management methods will all be part of the ecosystem in which this function operates.

The role of the prominent data engineer is to:

  • Large-scale data processing systems must be designed, built, and maintained. This gathers data from a variety of sources, both organized and unstructured. Data should be stored in a data warehouse or a data lake.

  • To construct data structures from raw data, use data processing transformations and algorithms. Put the results in a data warehouse or a data lake for further analysis.

  • Transform and combine multiple data sources into a scalable data repository (such as a data warehouse, data lake, cloud).

  • Recognize the various data transformation tools, methodologies, and algorithms available.

  • To transform acquired data into relevant and valuable information, use technical procedures and business logic.

  • This data must meet the requisite quality, governance, and compliance requirements for operational and business use to be regarded as trustworthy.