Data Engineer

Red Bull North America’s Data Science team is seeking a skilled Data Engineer to help build and scale the infrastructure powering our Data Science and Analytics initiatives. Reporting to the Director of Data Science, this role is ideal for an engineer who enjoys turning data science workflows into stable, reliable data, machine learning and generative AI processes, while also designing robust data models and validation frameworks. The candidate will leverage software development skills to establish best practices and standards for the data science team.

RESPONSIBILITIES
Areas that play to your strengths

All the responsibilities we’ll trust you with:
Expand all

• Responsibilities

  Design, develop, and maintain robust data and machine-learning / generative AI pipelines that support analytics, reporting, and business use cases.

  Productionize generative AI prototypes by transforming ad-hoc notebooks and experiments into secure, reliable, and repeatable workflows using modern DevOps practices.

  Implement and manage CI/CD pipelines, infrastructure-as-code, testing frameworks, and monitoring to automate deployment and lifecycle management of data and GenAI workloads.

  Collaborate with IT, BI, and data science teams to ensure that data models, pipelines, and GenAI services are designed for availability, scalability, maintainability, and accuracy.

  Tackle complex data integration challenges by applying ETL/ELT frameworks, advanced querying techniques, and sourcing from both structured and unstructured data.

  Build and maintain well-documented, structured data models and feature stores that enable efficient data science, generative AI experimentation, and analytics.

  Optimize, test, and debug machine-learning and generative AI workflows and pipelines in a cloud environment, ensuring performance, robustness, and cost efficiency.

  Establish and enforce engineering best practices, including code reviews, version control standards, automated testing, environment management, and release management.

  Develop and maintain data quality standards, observability, and data governance processes that enable trusted data to be used across the enterprise.

  Continuously monitor and optimize data pipeline performance to ensure efficiency, data quality, reliability, security, and compliance.

  Effectively communicate data models, datasets, and pipeline designs to data scientists, analysts, and business stakeholders in clear, accessible terms, providing comprehensive documentation and support.

  Help build and enhance data capabilities across the organization by ensuring teams are equipped with the right data, tools, and skills to effectively leverage them in support of the company’s data-driven and GenAI objectives.

EXPERIENCE
Your areas of knowledge and expertise

that matter most for this role:

• 3+ years of professional experience in software development, data engineering, business intelligence, data science, or a related field. Experience in the CPG industry is a plus.
• A bachelor’s or master’s degree in computer science, engineering, mathematics, or a related technical discipline is preferred.
• Experience with data modeling, cloud data warehousing (e.g., Snowflake or Databricks), and building ETL pipelines using tools such as dbt, AWS Glue, Dagster, or Airflow. Experience preparing data for machine learning model training and real-time applications is a plus.
• Proficiency in SQL and Python, with experience building robust ETL/ELT pipelines.
• Experience applying software engineering best practices to data engineering, including CI/CD, version control, and testing frameworks.
• Experience working with a major cloud platform such as AWS, Azure, or Google Cloud Platform (GCP).
• Experience using big data technologies.
• Knowledge of data management fundamentals and data storage principles.

• Travel 0-10%
• Permanent
• Benefits eligible

WHERE YOU’LL BE BASED
Santa Monica California , United States

United States Red Bull North America