About the Company
A global digital commerce and technology organization specializing in building data-driven platforms, analytics ecosystems, and intelligent automation solutions. With a strong presence across North America, Europe, and Asia, the company empowers leading consumer and retail brands to unlock insights, optimize operations, and enhance customer experience.
The team is driven by innovation, diversity, and collaboration — blending engineering, analytics, and cloud expertise to deliver scalable, secure, and high-performing digital solutions.
Position Overview
We are looking for a skilled Data Engineer to design, develop, and maintain data pipelines and warehouse infrastructure supporting global analytics initiatives. The ideal candidate will have deep expertise in Snowflake, ETL/ELT processes, and data architecture, with a passion for optimizing data systems that power real-time business intelligence and decision-making.
Key Responsibilities
- Design and build scalable data pipelines for high-volume data processing.
- Develop and maintain ELT/ETL workflows for integrating data from multiple sources.
- Optimize data infrastructure to ensure performance, availability, and reliability.
- Collaborate with analysts and data scientists to improve models and reporting accuracy.
- Implement data models to support business intelligence and analytics use cases.
- Ensure data governance, quality, and compliance across all systems.
- Automate recurring data workflows to enhance efficiency.
- Stay updated on emerging tools, technologies, and data engineering best practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
- 8+ years of experience as a Data Engineer, with strong expertise in Snowflake.
- Proven experience in Snowflake pipeline development and data architecture.
- In-depth knowledge of RBAC, virtual warehouses, streams, cloning, and time travel features.
- Advanced SQL development skills including stored procedures and performance tuning.
- Experience with Informatica, SnapLogic, or similar low-code ETL tools.
- Strong knowledge of data standardization, cleansing, and modeling.
- Proficiency in Python, Java, or C#.
- Familiarity with AWS, Azure, or GCP environments.
- Excellent analytical, problem-solving, and communication skills.