Principal Engineer, Data Platform

Keystone AI•Bellevue, WA

41d•$101,000 - $270,000

About The Position

Keystone.AI employs the world’s best AI/ML science and technology practitioners with unparalleled experience implementing highly complex, massive-scale algorithms and models to help companies make better decisions across manufacturing, supply chain management, sales, and marketing. We are seeking an experienced and visionary Principal Engineer – Data Platform to lead the architecture, development, and evolution of our next-generation data infrastructure. You will play a pivotal role in designing scalable and high-performance data solutions that empower analytics, AI/ML, and product development across the company. This is a high-impact role that combines technical leadership, strategic thinking, and cross-functional collaboration. You will leverage a deep understanding of machine learning, software engineering, and problem solving to build scalable, robust solutions for clients.

Requirements

10+ years in software engineering with at least 5 years focused on building and operating data platforms at scale.
Bachelor’s degree in computer science, Engineering, or a related field
Deep knowledge of distributed systems, data pipelines, data lake/warehouse architectures, and data modeling.
Is proficient in programming languages such in Python, Scala, or Java. Strong SQL skills. Experience with cloud platforms (e.g., AWS, GCP, Azure) and data orchestration tools.
Is familiar with cloud computing platforms and distributed computing frameworks
Proven ability to lead complex technical initiatives and influence stakeholders at all levels.
Is an excellent communicator and has strong teamwork skills to collaborate effectively with diverse stakeholders
Candidates must be authorized to work in the U.S. without sponsorship.

Nice To Haves

Experience with ML platform development or streaming data architecture
Contributions to open-source data tools or participation in industry forums
Experience in highly regulated or enterprise-scale environments

Responsibilities

Architect and Evolve the Data Platform: Design and implement robust, scalable, and secure data infrastructure that supports real-time and batch processing at scale.
Drive Technical Strategy: Lead the technical vision and roadmap for the data platform in alignment with product and business objectives.
Conducting thorough data analysis and pre-processing to ensure high-quality input for the models
Hands on development: Write high-quality, maintainable code and lead by example in system design, code reviews, and debugging.
Collaboration and Leadership: Work closely with data engineers, software developers, product managers, and scientists to deliver data solutions. Mentor and guide engineering teams.
Integrating machine learning solutions into existing systems and processes and scaling them for real-world applications
Operational Excellence: Ensure reliability, performance, and cost-efficiency of the data infrastructure. Define SLAs and lead incident response when needed.
Tooling and Innovation: Evaluate and integrate modern data technologies and frameworks (e.g., Apache Spark, Airflow, dbt, Kafka, Snowflake, etc.) to continuously improve platform capabilities.