Principal Data Engineer - Remote

Overview

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal Data Engineer in the United States.

This senior role offers the opportunity to lead the design and implementation of next-generation data and AI systems that support critical business operations at scale. You will shape the architecture for petabyte-scale ingestion, transformation, and analytics across multiple SaaS products, ensuring high-quality, reliable, and auditable data. This position blends hands-on engineering with strategic influence, including mentoring senior engineers, designing AI-driven data operations, and setting standards for semantic layers, metrics, and observability. It is ideal for someone passionate about AI, data quality, and building robust systems that empower both internal teams and customer-facing analytics. The role operates in a collaborative, innovative, and fast-paced environment, where technical leadership directly impacts business outcomes.

In Short

• Lead end-to-end data and AI architecture for large-scale ingestion, transformation, modeling, and serving pipelines.
• Design and maintain semantic layers, DBT models, metrics, and domain-specific definitions for both internal analytics and external reporting.
• Build and deploy AI agents for data quality, model creation, and operational efficiency.
• Ensure robust data quality, observability, and governance using rules, statistical methods, and ML techniques.
• Lead LLM data preparation, curation, and secure pipelines while enforcing compliance for sensitive data.
• Establish domain-driven standards including data contracts, SLOs, ownership, and documentation best practices.
• Optimize performance and cost of data systems, including Snowflake compute patterns, clustering, and caching strategies.
• Collaborate with product, engineering, and compliance teams to translate requirements into durable, auditable models and APIs.
• Mentor senior engineers, provide technical guidance, and drive adoption of best practices in data engineering and AI systems.

Requirements

• Proven experience in data engineering and architecture.
• Strong knowledge of AI systems and machine learning techniques.
• Experience with DBT and Snowflake.
• Ability to mentor and lead engineering teams.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.

Benefits

• Opportunity to work on cutting-edge data and AI technologies.
• Collaborative and innovative work environment.
• Competitive salary and benefits package.
• Professional development opportunities.