3 months ago
Responsibilities
- Define detailed data requirements with business customers and data analysts.
- Translate business challenges into logical and physical data models.
- Design and build scalable ELT/ETL pipelines using Airflow, BigQuery stored procedures, Dataflow, and Databricks.
- Lead development of analytical data models.
- Integrate SAP HANA, S/4HANA, Salesforce, and other SAP and non-SAP data sources.
- Optimize Google Vertex AI engineering and machine learning pipelines.
- Enforce data quality, reliability, governance, profiling, cleansing, standardization, and matching practices.
- Build data pipelines that load data into BigQuery.
- Own the existing Google BigQuery data warehouse infrastructure and related Google Cloud services.
- Assist ETL and BI developers with complex query tuning and schema refinement.
Requirements
- Bachelor’s degree in computer science or a related discipline.
- At least eight years of data engineering experience, primarily with Google BigQuery.
- Expertise writing, analyzing, and tuning complex SQL queries.
- Extensive Python programming experience.
- Hands-on experience with Google Cloud Platform, BigQuery, Airflow, and Dataflow.
- Understanding of dimensional modeling and ER modeling.
- Experience extracting data from SAP HANA and Salesforce.
- Experience with Java and NodeJS.
- Preferred experience with SAP Datasphere, Terraform, Docker, and CI/CD.
- Ability to adopt unfamiliar tools and learn new programming languages.
- Strong problem-solving ability and a positive attitude.
Categories
Data Engineering
About YETI
YETI designs and sells durable hard and soft coolers, insulated drinkware, bags, and outdoor accessories for outdoor enthusiasts and working professionals. Founded in 2006 and headquartered in Austin, Texas, it goes to market through direct-to-consumer e-commerce, its own retail stores, and specialty and big-box retailers. Its products include rotomolded coolers and vacuum-insulated tumblers used in hunting, fishing, camping, and worksite settings.