A data engineer designs and builds systems that collect, store, manage and analyze data. Companies collect a lot of information about their business from various resources, and they need data engineers to make this information accessible, structured and usable. A data engineer can build data pipelines, optimize queries, create automated systems, manage data warehouses, and develop data workflows.
Roles of a Data Engineer
• Build data pipelines – this involves collecting data and building data warehouses or data lakes.
• Make data accessible – involves remodeling the data in a way that is easy for all stakeholders to access interpret and manipulate. Excel, Power BI, and Tableau are some of the tools mostly used.
• Optimize queries – involves updating the current queries to meet current business needs.
• Data maintenance – involves testing and maintenance to ensure the system is running smoothly.
Skills needed
- Distributed systems: Hadoop
- Databases: MySQL
- Data processing: Spark
- Real-time data ecosystem: Kafka
- Data orchestration: Airflow
- Data science: pandas (Python library)
Software and Technology Requirements
- Cloud account - Google GCP, AWS or Azure.
- Python 3, Python IDE and a text editor - VSCode, Anaconda.
- SQL server and MYSQL Workbench or DBeaver and DBVisualizer.
- Git and version control system
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