Summary
A Data Engineer is responsible for designing, building, testing, and maintaining data pipelines, databases, and data storage systems. They work closely with Data Scientists, Data Analysts, and other stakeholders to ensure data is available, reliable, and efficiently processed for business insights and analytics purposes.
Responsibilities
Design and implement scalable data architectures using data warehousing techniques.
Develop and maintain ETL processes to facilitate the efficient extraction, transformation, and loading of data.
Implement and maintain data pipelines with a focus on automation and integration within a DevOps framework.
Collaborate with Data Scientists, Data Analysts, and other stakeholders to define data requirements and data models.
Collaborate with cross-functional teams in an Agile environment to define data requirements and improve data functionality.
Optimize and fine-tune data processing and storage systems for performance and scalability.
Implement data validation, quality checks, and monitoring to ensure data accuracy and integrity.
Troubleshoot and resolve data-related issues, maintaining documentation and change management processes.
Participate in evaluating and adopting new data engineering tools, technologies, and best practices.
Qualifications and Requirements
Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
2-5 years of experience in data engineering or a related field.
Proficiency in SQL and at least one programming language, such as Python or Java.
Experience with big data technologies, such as Hadoop, Spark, or similar.
Proven experience in data warehousing, ETL development, and data modeling.
Strong understanding of Agile methodologies and experience in a DevOps culture.
Familiarity with cloud-based data storage and processing platforms, such as AWS, Azure, or GCP.