Data Engineer

This is a remote position.

Job Summary: We are seeking a skilled Data Engineer to design, develop, and maintain the data infrastructure for a revolutionary scientific computing platform. You will be responsible for ensuring efficient data storage, retrieval, and processing, leveraging your expertise in data management, database technologies, and data processing pipelines. Your role is crucial in building a robust and scalable data infrastructure that supports the platform's scientific computations.

Responsibilities:

• Design and implement the data architecture for the platform, ensuring scalability, security, and data integrity.
  
• Develop and maintain data pipelines for data ingestion, transformation, and loading, ensuring efficient data flow and processing.
  
• Manage and optimize databases, including relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra), to ensure data availability and performance.
  
• Implement data security measures, including encryption, access control, and data masking, to protect sensitive data.
  
• Monitor data quality and ensure data consistency, implementing data validation and cleansing processes.
  
• Collaborate with other team members, including the Tech Lead, ML/AI Engineer, and Backend Engineer, to ensure seamless data integration and processing.
  
• Stay up-to-date with the latest data management technologies and best practices.
  

Requirements:

• Bachelor's degree in Computer Science, Data Science, or related field can be considered an advantage..
  
• 5+ years of experience in data engineering, with a focus on building and managing data infrastructure for scientific computing applications.
  
• Proficiency in data management tools and technologies (SQL, NoSQL, Hadoop, Spark, etc.).
  
• Experience with data warehousing and data lake concepts.
  
• Experience with cloud data services (AWS Redshift, Azure SQL Database, GCP BigQuery).
  
• Strong understanding of data security principles and best practices.
  
• Experience with distributed computing environments and resource management.
  
• Experience with local development tools like data modeling tools, data processing frameworks, and data visualization tools for setting up and managing data development environments.