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

Excellent analytical skills with a balance of quantitative rigor and qualitative insight

Highly proficient in Microsoft Office and Google Suite for documentation and collaboration

Bachelor’s and/or Master’s degree in Computer Science or a related technical field

Agile, innovative, and solutions-oriented thinker with a strong sense of ownership

Collaborative and dependable team player, effective in multicultural and diverse environments

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