What You’ll Do:

• Design and build scalable and robust data pipelines to collect, process, and distribute large volumes of data efficiently
• Build ETL pipelines that will enable and streamline regular reporting on SLAs
• Provide clear documentation on data models with source, description and field definitions for better collaboration, maintainability, and usability
• Provide recommendations and guidance related to data integration strategy in order to meet future analytic and model needs
• Make our data more discoverable and easier to use for analytics and Machine learning modeling
• Modify and improve data engineering processes to handle ever larger, more complex, and more types of data sources and pipelines.
• Work with AI/ML teams to understand their business and technical problems and deliver data to support the solutions to those problems
• Incorporate core data management competencies including data governance, data security and data quality.
• Test data movement, transformation code, and data components.

What You’ll Have:

• Bachelor’s Degree in STEM related field or equivalent
• Three years of data engineering or equivalent experience
• Proven experience designing and implementing scalable, performant data pipelines, data services, and data products
• Built and maintained data warehouses with ETL/ELT pipelines
• Experience with data modeling, data lakes, and warehouse design
• Experience with various databases and datawarehouses such as Redshift and Snowflake
• Background in ETL and data processing, familiar with how to transform data to meet business goals
• Experience working with Fivetran and DBT is a bonus
• Strong knowledge of SQL and Python
• Strong problem solver who ensures systems are built with longevity and creates innovate ways to resolve issues.
• Have strong communication skills to collaborate with cross-functional partners and drive projects