Overview:

• Build and maintain data pipelines for attribution modeling, experimentation, and causal analysis.
• Develop and optimize data models and semantic layers for performance measurement.
• Collaborate with data scientists to operationalize experimental designs and measurement frameworks.
• Ensure data quality, consistency, and accessibility across platforms.
• Implement scalable solutions using Databricks and Redshift.
• Translate business requirements into technical specifications.

Qualifications:

• Bachelor’s degree in Computer Science, Statistics, Economics, or a related field.
• 5–10 years of experience in analytics engineering or data infrastructure.
• Proficiency in SQL and experience with Databricks and Redshift.
• Experience with Python for data transformation and validation.

Qualifications:

• Advanced degree (Master’s or PhD) in Data Engineering, Computer Science, Statistics, Economics, or a related field.
• Experience supporting measurement science initiatives, including causal inference and experimentation.
• Familiarity with AWS-based infrastructure and tools like Airflow or dbt.
• Experience in the alcohol beverage industry or similar consumer sectors.