
Data Engineer for Scientific Research and Analytics
2 days ago
As a Data Engineer, you will play a pivotal role in designing and building data lake solutions for scientific research. This position involves creating scalable and high-performance data engineering solutions for large datasets and collaborating with research scientists to understand their needs.
Key Responsibilities- Data Engineering: Design, develop, and implement data pipelines, ETL/ELT processes, and data integration solutions that meet the demands of complex scientific research.
- Data Modeling & Optimization: Contribute to data models and dictionaries to ensure data accuracy and consistency across the organization.
- Collaboration & Innovation: Collaborate with cross-functional teams, including research scientists, to design data-driven solutions and explore new tools and technologies to improve data platform performance.
- Cloud & Security: Leverage cloud platforms (AWS preferred) to build efficient and secure data solutions, ensuring data security and privacy measures are in place to protect sensitive information.
- A Bachelor's degree with 0-3 years of experience or a Diploma with 4-7 years of experience in Computer Science, IT, or a related field.
- Proficiency in SQL and Python for data engineering tasks.
- Hands-on experience with big data technologies like Databricks and Apache Spark.
- A strong understanding of data modeling, data warehousing, and data integration concepts.
- Experience with relational databases (Oracle, MySQL, SQL Server, PostgreSQL).
- Knowledge of cloud data platforms (AWS preferred).
- Databricks Certified Data Engineer Professional certification is an advantage.
- Problem-Solving: Excellent critical-thinking and problem-solving skills, with the ability to work with large, complex datasets.
- Communication: Strong communication and collaboration skills, with demonstrated awareness of how to function in a team setting.
- Initiative: A high degree of initiative and self-motivation, with a passion for tackling complex challenges.
- Adaptability: The ability to learn new tools and technologies to improve platform performance.
This is a unique opportunity to join a forward-thinking organization and contribute to cutting-edge scientific research. If you have a passion for data engineering and a drive to innovate, we encourage you to apply for this challenging role.
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