Overview
Skills
Job Details
Role: Data Engineer
Hybrid in Seattle, WA
Solid Experience with Modern Data Platforms: Hands-on experience with cloud-native solutions, Data Bricks, and Snowflake for scalable data processing and machine learning operations.
Expertise in Scripting and Data Analysis: Strong proficiency in scripting for data analysis and automation, with a deep understanding of SQL and experience in Python for data operations.
Advanced Data Management Experience: Minimum of 3 years proven experience in designing, managing, and optimizing data warehouses and complex ETL workflows, preferably with experience in modern ETL tools and practices.
Analytical Acumen: Robust analytical skills to derive insights from data, support Business Analysts, and contribute to data-driven decision-making processes.
Problem-Solving Expertise: Advanced problem-solving abilities with a strong foundation in mathematical principles applicable to data modeling and machine learning.
Backend Development Skills: Experience in backend development, particularly with PL/SQL, and an openness to adopting new programming paradigms.
Cloud Proficiency: Strong working knowledge of cloud platforms such as AWS, Azure, and Google Cloud Platform, with a focus on leveraging cloud services for data solutions.
Big Data Expertise: Extensive experience with big data technologies and methodologies, skilled in handling large-scale data manipulation and analysis.
ML/Ops and DevOps Integration: Familiarity with modern operational practices including ML/Ops and DevOps, with a track record of improving pipeline efficiency and deployment.
Industry Experience: Retail industry experience preferred, with fashion retail experience highly desirable.
Data Architecture Insight: Knowledge of data architecture principles, especially in environments using Oracle Retail Management Systems or similar platforms, is a plus.