Roles and responsibilities:
As a Data Engineer, you will play a crucial role in optimizing our data ecosystem to bolster analytical insights and inform strategic decisions. Key responsibilities include but are not limited to the following:
- Plan, execute, and manage ETL processes, data models and data integration. Maintain the highest standards of data accuracy, integrity, and accessibility by employing robust data governance practices.
- Perform in-depth analysis of company data to identify trends, uncover hidden patterns and provide deeper insights for business strategies and decisions.
- Work closely with various departments to understand their data requirements and challenges. Provide expert advice and analytics solutions that align with departmental and organizational goals.
- Monitor data pipelines, databases, and analytical operations to guarantee their continuous functionality. Swiftly detect and resolve data-related issues and performance constraints.
- Keep abreast of the latest trends and best practices in data engineering. Suggest and apply improvements to enhance data quality, operational efficiency, and performance.
Requirements:
- Possession of a Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
- Proficient in SQL and at least one programming language (Python, C++, or R) for advanced data analysis and engineering tasks.
- Solid background in ETL processes, data warehousing, data modelling, and integration solutions. Experience with cloud data platforms (Snowflake, Kafka, or similar) is a significant advantage.
- Strong ability to use data visualization tools (Tableau, Power BI, or similar) to craft engaging visual stories and reports from data.
- A good understanding of data science methodologies, including machine learning and deep learning, is highly desirable.
- With exceptional problem-solving skills, outstanding communication, and a strong aptitude for teamwork.
