Why This Role Stands Out
This hybrid Staff Data Engineer role at Southern Glazer's Wine & Spirits offers a fantastic opportunity to design and optimize scalable data platforms, impacting critical business operations and mentoring a high-performing data team. You'll thrive here if you're a seasoned data engineer passionate about building robust data solutions, driving best practices, and contributing to a dynamic, people-first culture. Apply now to leverage your expertise in cloud data warehousing and data pipeline development within a leading industry company.
Quick Overview
Job Description
Southern Glazer's Wine & Spirits seeks a Staff Data Engineer to design and optimize scalable data platforms supporting wholesale distribution, sales, and supply chain analytics. You will own end-to-end data pipelines, from ingestion and modeling to performance tuning and governance across cloud data warehouses. Partner with analytics, IT, and business stakeholders to deliver trusted datasets, real-time reporting, and advanced analytics capabilities. Mentor other engineers, champion best practices, and help shape a people-first, high-performing data culture in a fast-paced environment.
Responsibilities
- Design, build, and maintain scalable, secure data pipelines and integrations across enterprise systems
- Develop and optimize cloud-based data warehouses, models, and schemas to support analytics and reporting
- Implement data quality checks, monitoring, and governance to ensure reliable, trusted datasets
- Collaborate with analytics, IT, and business teams to translate requirements into robust data solutions
- Mentor and guide other data engineers, promoting best practices, standards, and code reviews
- Support advanced analytics, BI, and data science initiatives with well-structured, performant data
- Troubleshoot and resolve data issues, performance bottlenecks, and pipeline failures in a timely manner
Required Skills
- Data pipeline design and development
- SQL and performance tuning
- Cloud data warehousing (e.g., Snowflake, Redshift, Big
- Query)
- ETL/ELT tools (e.g., dbt, Airflow, Informatica)
- Data modeling (star, snowflake, normalized models)
- Python or Scala programming
- Data governance and data quality frameworks
- Batch and streaming data processing
- Version control and CI/CD for data projects
- BI/reporting integration and data serving
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