Principal Data Engineer

Utilidata

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.

Posted 5/12/2026full-timeRemote • 🇺🇸 United StatesLead💰 $170,000 - $210,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringdata pipeline designdata modelingdata transformationdata ingestiondata storagedata servingcloud data infrastructurebatch processingstreaming processing

Soft Skills

leadershipmentoringcommunicationproblem-solvingcollaborationtechnical depthdecision-makingplanningdocumentationrisk management