Data Engineer

This is a remote position.

The Data Engineer is responsible for developing, maintaining, and optimizing data pipelines and infrastructure to support analytics, business intelligence, and data science initiatives. This includes integrating various data sources, ensuring data quality, and implementing ETL processes. The ideal candidate should have a solid foundation in programming, databases, and cloud-based solutions, with a strong willingness to learn and adapt in a fast-paced environment. 

Job Responsibilities 

• Design, build, and maintain efficient and reliable data pipelines using SQL, Python, and cloud-based technologies. 
  
• Support the integration of multiple data sources into centralized storage and analytics systems. 
  
• Perform data cleansing, transformation, and validation to ensure data accuracy and reliability. 
  
• Collaborate with data scientists, analysts, and other engineers to ensure data availability for analytics and modeling. 
  
• Monitor and optimize existing ETL processes to improve performance and scalability. 
  
• Assist in implementing data models to support reporting, dashboards, and predictive analytics. 
  
• Apply software engineering best practices in code development, version control, and testing. 
  
• Research and learn new data tools and techniques to enhance existing processes. 
  
• Maintain clear, concise, and up-to-date technical documentation for data workflows. 
  
• ​Troubleshoot and resolve data-related issues promptly and effectively. 
  
  

Requirements

• Proficient in Python for scripting, automation, and data processing. 
  
• Solid understanding of SQL and relational database concepts. 
  
• Familiarity with ETL tools (e.g., Airflow, Alteryx, or similar). 
  
• Basic knowledge of cloud platforms (AWS, GCP, or Azure) for data storage and processing. 
  
• Understanding of data modeling concepts and best practices. 
  
• Knowledge of data visualization tools is a plus (e.g., Tableau, Power BI, or similar).