Data Engineer

Role of a Data Engineer

Resources:

• Link

Primary Goal:
The primary responsibility of a data engineer is to take data from its source and make it available for analysis. They focus on automating the data collection, processing, and analysis workflows while solving how systems manage and handle the flow of data. Work in Data Engineering.

Key Responsibilities:

1. Infrastructure Design and Maintenance:
   Data engineers design, build, and maintain the necessary infrastructure to collect, process, and store large amounts of data. This infrastructure is crucial for ensuring data is accessible and usable for analysis and reporting.

2. Data Pipelines: They develop data pipelines that integrate data from various sources, ensuring data quality, consistency, and timely availability for downstream use, such as analytics and reporting.

3. Support Role:
   Data engineers act as a bridge between ==data producers and consumers==, ensuring smooth and reliable data flow. They support business operations through scalable and efficient Data Management solutions, contributing indirectly to product delivery and decision-making.

Core Activities:

• Build and Optimize Systems:
  Design and optimize systems that allow analysts and other consumers to access well-organized, high-quality data.

• Pipeline Development and Testing:
  Develop, test, and maintain data pipelines to manage data flows efficiently. This includes integrating with external APIs and ensuring data is prepared for further analysis.

What engineers do & interact with:

• Batch Processing
• Data Streaming
• Big Data
• Distributed Computing
• Storage solutions
• ETL
• Data Warehouse
• SQL
• Command line
• Data storage
• Full Lifecycle Management

Stakeholders they interact with:

• Data Scientists: Collaborate to provide data pipelines and pre-processed data for advanced analytics.
• Business Analysts: Ensure data is structured and accessible for analysis and reporting.
• Senior Stakeholders and Business Ambassadors: Communicate requirements, progress, and solutions to align with business goals.
• Software Engineers and Data Teams: Coordinate on data production and integration processes.

Tasks They Are Usually Given

• Project Management: Tracking tasks, bugs, and progress through Azure Boards.
• Collaboration: Facilitating teamwork with shared repositories and continuous integration workflows.
• Continuous Learning: Keeping up-to-date with the latest technologies and updating pipelines due to obsolescence of tech
• Documentation and Security: Creating documentation, implementing security measures, and exploring system upgrades for enhanced efficiency.

Tools they use:

• Snowflake: Cloud-based data warehousing for scalable storage and processing.
• Microsoft SQL Server: SQL-based relational database management.
• Azure SQL Database: Managed relational database service on Azure.
• Azure Data Lake Storage: Scalable storage for big data analytics.
• SQL and T-SQL: Query languages for managing and querying relational databases.
• AWS S3: Storage for data lakes.