Principal Engineer - Data Platforms

Dutch Bros Coffee•Tempe, AZ

1d•Hybrid

About The Position

It's fun to work in a company where people truly believe in what they are doing. At Dutch Bros Coffee, we are more than just a coffee company. We are a fun-loving, mind-blowing company that makes a difference one cup at a time. Position Overview: As the Principal Engineer in the Enterprise Data Platform, you will lead the modernization and optimization of Dutch Bros’ foundational data ecosystem. In this high-impact, hands-on individual contributor role, you will design and operate scalable, resilient infrastructure to power distributed analytics, machine learning, and AI-driven workflows. You are a builder at heart—responsible for writing proof-of-concepts, defining rigorous coding standards, and championing AI-assisted development tools that reduce toil and accelerate team velocity. By partnering with other principal engineers and mentoring the broader team, you will bridge the gap between high-level architecture and seamless execution to deliver a world-class, self-service data experience for the entire organization.

Requirements

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
15+ years of software engineering experience, with a minimum of 10 years specializing in backend distributed systems or data infrastructure at scale.
Expert-level Python and SQL proficiency (10+ years) rooted in a career of building production-grade software.
Proven track record of designing large-scale data platforms with a deep understanding of CAP theorem, eventual consistency, and the trade-offs between batch and streaming architectures.
Hands-on mastery of Snowflake (internals and clustering), dbt (macro design and Jinja), Airflow (scheduler internals), and Power BI (Import vs. Live connection).
Comprehensive knowledge of AWS services, including IAM, VPC, Glue, S3, SFTP, Lambda, CloudWatch, and SNS.
Experience implementing Gitlab CI/CD and DataDog for robust system monitoring and alerting.
Ability to design RAG architectures, manage vector databases, and integrate LLMs into complex data pipelines.
Skilled in writing persuasive RFCs and ADRs that drive consensus among architects and engineering leadership.
Proven ability to influence technical strategy and facilitate cross-functional alignment across organizational levels without direct managerial authority.

Responsibilities

Technical Strategy & Platform Architecture Define the long-term technical architecture for the Enterprise Data Platform, translating business strategy into scalable Data Mesh and domain-oriented specifications.
Implement automated CI/CD pipelines and Infrastructure as Code (IaC) to foster a unified engineering culture across disciplines.
Design robust APIs that enable seamless data consumption across operations, finance, and product teams.
AI-Assisted Development & Integration Lead the integration of AI-assisted development (Cursor, MCP, Copilot) to accelerate developer velocity and reduce cognitive load.
Scale LLM-driven code generation for AWS data pipelines, including automated test creation, documentation, and semantic schema generation.
Leverage Amazon Bedrock, Snowflake Cortex, and AI-enabled IDEs to optimize the data lifecycle and reduce delivery lead times.
Data Engineering at Scale Build resilient ELT/ETL pipelines utilizing S3, Lambda, Glue, dbt, and Airflow (MWAA).
Establish data quality, observability, lineage, and SLAs as core, first-class features of the data platform.
Standardize enterprise-wide schema design, modeling patterns, and deployment workflows.
Machine Learning & Infrastructure Design and productionize end-to-end ML infrastructure, including feature stores, model experimentation frameworks, and deployment monitoring.
Build optimized ETL/ELT workflows for training data and model deployment leveraging Snowflake ML (Snowpark) and Amazon SageMaker.
Engineering Standards & Technical Influence Enforce high standards for code quality through rigorous PR reviews, unit testing, and automated schema validation within CI/CD pipelines.
Architect SRE-focused resiliency frameworks and self-healing systems to ensure 99.9% availability for critical data pipelines.
Partner with Data Science, Product, and Platform teams to align on performance, compliance, and feature engineering.
Mentor Senior and Lead engineers through design reviews, RFCs, and pair programming to elevate the organization's technical bar.
Semantic Engineering & Graph RAG Lead the design and POC of Graph RAG (Retrieval-Augmented Generation) architectures, enabling LLM agents to query structured Snowflake data via Knowledge Graphs.
Apply knowledge of open-source Knowledge Graph solutions to create advanced patterns for semantic data retrieval.
Coordinate project testing, deployment, and post-implementation activities, ensuring successful project delivery and that lessons learned are applied to future projects.