Principal Data Engineer
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Job Description
Principal Data Engineer overseeing technical direction for AI data center engineering platform at NVIDIA-backed company. Responsible for architecture, design decisions, and mentoring the team in data infrastructure.
Responsibilities:
- Architect and contribute directly to core platform components, including ingestion pipelines, transformation frameworks, data models, and orchestration
- Define and evolve the multi-quarter technical roadmap for the data platform, balancing new capabilities, reliability investments, and technical debt reduction in alignment with the broader platform architecture
- Drive evaluation and adoption of tooling across the stack, ensuring choices are well-reasoned and aligned with where the platform needs to go
- Lead architecture reviews and design discussions, ensuring decisions are well-reasoned, documented, and understood by the team
- Cut through ambiguity by asking the right questions early about data quality, schema evolution, and downstream dependencies, and identify risks before they become crises
- Translate complex data infrastructure decisions for non-technical stakeholders without oversimplifying, and break vague product requirements into clear engineering tasks and acceptance criteria
- Partner closely with data science leads and cross-functional teams to surface dependencies and constraints early and prioritize improvements that unlock productivity
- Run a lightweight but effective backlog and planning process, keeping the team focused and unblocked
- Mentor and grow engineers with an emphasis on raising technical depth — delegate meaningful work, pair on hard problems, and create opportunities for others to stretch
- Set code review standards, testing philosophy, and engineering best practices that make the whole team better, including data validation, pipeline testing, and schema management
- Ensure data systems work reliably in production — instrumented, observable, and operable, with clear SLAs on freshness, completeness, and accuracy
Requirements:
- At least 8 years of experience in data engineering, with 2+ years operating at a principal or staff level
- Proven ability to design and evaluate end-to-end data platforms across ingestion, transformation, storage, and serving, with clean contracts between layers
- Deep understanding of data pipeline design, with fluency in the patterns and tradeoffs of batch and streaming pipelines at scale
- Strong understanding of data modeling and storage strategies
- Strong software engineering fundamentals, with the depth to evaluate code quality and set architectural standards
- Strong experience with cloud data infrastructure (AWS, GCP, or Azure) and the surrounding ecosystem
- Demonstrated ability to lead technical teams, set direction, and grow engineers without relying on formal authority.
Benefits:
- Competitive compensation and benefits, including health, dental, vision, and employer-match 401k
- Flexible work environment with flexible paid time off
- Providing mentorship and growth opportunities as part of a collaborative team
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