Senior Data Engineer

This is a remote position.

The Senior Data Engineer is responsible for preparing data for modeling and predictive analytics. This includes integrating new data sources, performing pre-processing operations such as data cleansing, feature engineering, statistical analysis, and sampling, as well as managing a wide range of ETL-related tasks. The ideal candidate should demonstrate strong software development practices and a continuous learning mindset. Proficiency in Python, machine learning, data storage solutions, and ETL pipeline development is essential.  

Job Responsibilities:

• Design and implement scalable data pipelines using SQL, Airflow, Python, Alteryx, and cloud-based technologies  
• Lead the integration of data sources and design data models to meet complex business needs  
• Ensure data quality by identifying issues and collaborating with source owners to implement preventive measures  
• Deploy and optimize machine learning models, statistical methods, and analytics programs  
• Research new data acquisition methods and innovative uses of existing data to drive business value  
• Integrate advanced data management tools and software engineering practices to enhance system performance  
• Build and maintain high-quality datasets to support decision-making and data-driven products  
• Develop custom software components and analytics applications aligned with business requirements  
• Implement strategies to improve data reliability, efficiency, and scalability  
• Drive innovation through R&D initiatives within the data engineering team  
• Collaborate cross-functionally to build a flexible, scalable, and high-performing data platform  
• ​ Maintain clear and comprehensive technical documentation for ongoing projects  

Requirements

• Proficient in Python, with hands-on experience in data analysis and automation  
• Skilled in using Dataiku for advanced data workflows and machine learning applications  
• Familiarity with cloud services like AWS or Azure.
• Strong background in data visualization and statistical analysis to drive data-driven insights  
• Practical experience with machine learning models and managing large-scale (big data) projects  
• Solid understanding of programming concepts and data architecture principles  
• Capable of defining and tracking meaningful metrics for data and analytics initiatives