The Data Engineer will play a pivotal role in transforming raw data into reliable, analytics-ready products that people actually use to make decisions, building and maintaining the pipelines, Snowflake data models, and dbt-based transformation layers that serve as the backbone of our analytics and AI ecosystem.
The ideal candidate will have hands-on experience with Snowflake, dbt, Dagster, and Python to develop, implement, and maintain robust data pipelines and analytical solutions. The engineer will interact directly with business stakeholders, transforming business requirements into technical solutions. Service mindedness, a white-glove-service approach, communication skills, and pro-activity are key skills required for the right candidate.
This position is on the Red Bull North America HQ Talent team and will be required to sit onsite in our North American Headquarters office, in Santa Monica, CA. We are in the office 4 days per week with the 5th business day being remote.WHAT SUCCESS LOOKS LIKEPipelines run reliably with high data quality and minimal rework
Transformation models are clean, tested, and documented to team standards
AI-ready data layers are in place and accelerating intelligent analytics delivery on Snowflake Cortex
Business teams receive accurate, well-documented data products without needing to re-open requirements
RESPONSIBILITIESAreas that play to your strengthsAll the responsibilities we'll trust you with:
- DATA ENGINEERING
Design, build, and maintain data pipelines using modern orchestration tools (e.g., Dagster, Airflow, or equivalent)
Develop and optimize Snowflake data models - including dynamic tables, streams, tasks, and materialized views - for performance and reliability
Ingest and process structured and semi-structured data (CSV, JSON, Parquet) via automated ELT workflows
Write Python for data manipulation, automation, and pipeline development - following engineering best practices including testing, documentation, and code optimization
Manage version control and collaboration through GitHub, adhering to branching strategies and code review standards
Build and maintain CI/CD pipelines to automate testing, validation, and deployment of data assets
Contribute to data lake design and maintenance, ensuring data integrity, lineage, and quality standards - AI & DATA INTELLIGENCE
Build clean, AI-ready data layers that support agentic analytics and intelligent querying use cases on Snowflake Cortex
Contribute to semantic layer development alongside senior engineers, supporting clean, consistent data access patterns for AI and analytics consumers
Support the team's work in AI for analytics on Snowflake Cortex - executing on agent-driven workflows and automated insight pipelines under the guidance of senior engineers - QUALITY & CONTINUOUS IMPROVEMENT
Monitor and troubleshoot pipelines to ensure uptime, data quality, and SLA compliance
Implement testing frameworks within your transformation layer to validate accuracy and catch issues early
Identify opportunities to optimize pipeline performance, reduce latency, and lower compute cost - COLLABORATION & STAKEHOLDER PARTNERSHIP
Partner with business analysts and Sales, Distribution, Operations, and Finance teams to translate requirements into technical solutions
Engage business stakeholders with a service-first mindset - proactively communicating, setting clear expectations, and following through
Document pipeline designs, data flows, and technical decisions to support team knowledge and auditability
Build relationships with global data engineering teams to align on standards and shared solutions - ROADMAP & INNOVATION
Contribute to the Analytics roadmap for short, medium, and long-term business needs
Innovate and enhance our data lakes and data fabric, ensuring alignment with business goals
Stay current with industry trends and emerging technologies, particularly in the Snowflake ecosystem and AI-driven analytics - WAYS OF WORKING
Own your work end-to-end - manage priorities, track commitments in Jira, and don't wait to be asked
Collaborate openly across engineering, analytics, and business teams in a high-trust, low-bureaucracy environment
Bring a white-glove mindset to business stakeholders - responsive, clear, and solutions-oriented
EXPERIENCEYour areas of knowledge and expertisethat matter most for this role:
- 3+ years of experience in data engineering or analytics engineering
- Bachelor's degree or higher in Computer Science, Information Systems, Data Engineering, or a related field.
- Hands-on experience with a modern cloud data warehouse platform (e.g., Snowflake, Databricks, or equivalent): SQL, data modeling, and performance tuning
- Working proficiency with a SQL-based data transformation framework (e.g., dbt or equivalent)
- Experience with a workflow orchestration tool (e.g., Dagster, Airflow, Prefect, or equivalent)
- Python proficiency: data manipulation, scripting, pipeline development, and Git-based version control
- Experience with GitHub and CI/CD pipeline tooling for data asset deployment
- Familiarity with cloud storage and compute services (e.g., AWS, Azure, or GCP)
- Experience with agentic AI frameworks like Snowflake Cortex or equivalent is a strong plus
- Strong communication skills; proactive, collaborative, and service-minded
- Demonstrated ability to work effectively with business users at all levels
- High level of responsibility and accountability, with a commitment to delivering high-quality solutions
- Willingness to travel as needed for onboarding and collaboration with global teams
- Fluent in English; additional language skills an advantage.
- Travel 0-10%
- Permanent
- Benefits eligible
WHERE YOU'LL BE BASEDSanta MonicaCalifornia, United StatesUnited StatesRed Bull North America
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