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Principal Data Platform Engineer Jobs (NOW HIRING)

A Place For Mom

Principal Data Engineer, Data Platform

$170K - $195K/yr

We are seeking a Principal Data Engineer to help define and evolve our enterprise data platform strategy, with Databricks serving as the foundation for analytics, AI, machine learning, governance ...

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Exactera

Staff Data Engineer

San Diego, CA

$121K - $146K/yr

You will own a defined slice of our centralized Databricks data platform with full accountability for decisions and delivery, serve as a technical counterpart to the Principal Data Platform Engineer ...

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Principal Data Platform Engineer information

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$74K

$147.2K

$212.5K

How much do principal data platform engineer jobs pay per year?

As of Jun 14, 2026, the average yearly pay for principal data platform engineer in the United States is $147,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is the difference between Principal Data Platform Engineer vs Data Engineer?

AspectPrincipal Data Platform EngineerData Engineer
CredentialsBachelor's/Master's in CS, Data Science, or related; often with certifications in cloud platformsBachelor's in CS, Data Science, or related; certifications are common but not mandatory
Work EnvironmentDesigns and oversees data platform architecture, leads technical strategyBuilds, maintains, and optimizes data pipelines and databases
Employer & Industry UsageUsed in large tech, finance, and enterprise companies focusing on scalable data solutionsCommon across industries for data processing and analytics tasks

The Principal Data Platform Engineer focuses on designing and leading the development of data platforms, ensuring scalability and performance. In contrast, Data Engineers primarily build and maintain data pipelines and infrastructure. Both roles require strong technical skills, but the Principal role involves strategic oversight and architecture leadership.

More about Principal Data Platform Engineer jobs
What cities are hiring for Principal Data Platform Engineer jobs? Cities with the most Principal Data Platform Engineer job openings:
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Principal Data Platform Engineer jobs near you
Infographic showing various Principal Data Platform Engineer job openings in the United States as of June 2026, with employment types broken down into 31% Full Time, 60% Part Time, and 9% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $147,220 per year, or $70.8 per hour.
Principal Data Platform Engineer

Principal Data Platform Engineer

MedRisk LLC

Conshohocken, PA • On-site

Full-time

Posted 21 days ago

MedRisk rating

8.0

Company rating: 8.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

97th of 427 rated business services

Job description

Position Summary

The Principal Data Platform Engineer is a senior individual contributor who defines and owns the technical vision, architecture, and evolution of the enterprise data platform. This role is responsible for platform-wide design decisions that enable trusted analytics, business intelligence, and AI/ML use cases at scale.

Serving as the technical leader for data platform and data engineering capabilities, this role designs and governs scalable, reliable, and well-modeled data assets that support analytics, data science, and AI workloads. The Principal Data Platform Engineer partners closely with delivery leadership and hands-on practitioners across the Data and AI organization to ensure the platform balances near-term delivery needs with long-term scalability, reliability, and maintainability.

Operating across multiple scrum teams, this role acts as a force multiplier by establishing standards, reusable patterns, and self-service capabilities that improve data quality, accelerate delivery, and increase the overall effectiveness of analytics and AI initiatives.

Primary Duties & Responsibilities

  • Own the technical architecture and long-term roadmap of the enterprise data platform supporting both Analytics/BI and AI/ML workloads.
  • Design and evolve data ingestion, transformation, and orchestration patterns that support scalable, reliable, and auditable data pipelines.
  • Define and enforce standards for data modeling, including curated analytical datasets, semantic models, and ML-ready / feature-ready datasets.
  • Lead platform and architectural design reviews across multiple cross-functional scrum teams, influencing solutions without direct authority.
  • Establish platform patterns for data quality, observability, lineage, and reliability to ensure trust in downstream analytics and AI systems.
  • Partner with AI Engineers and Data Scientists to enable efficient feature engineering, model training, and inference through well-designed data assets.
  • Serve as the technical authority for Microsoft Fabric, Power BI, and associated data platform components, ensuring best practices are consistently applied.
  • Enable self-service analytics and data science by delivering reusable data products, documentation, and clear consumption contracts.
  • Mentor data engineering team members, raising the overall technical maturity of the organization.
  • Balance immediate delivery needs with long-term platform scalability, performance, and maintainability considerations.
  • Evaluate and recommend new platform capabilities, tools, and architectural approaches aligned with organizational strategy.

Qualifications

  • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
  • 10+ years of experience designing and building modern data platforms in production environments.
  • Deep expertise in data architecture, data modeling, and distributed data processing for analytics and AI/ML use cases.
  • Strong experience with modern cloud data platforms, including managing and optimizing compute, storage, networking, security, and cost governance; Microsoft Fabric and Power BI experience is highly valued.
  • Proven ability to design platforms that support both BI/analytics workloads and ML/AI pipelines at scale.
  • Experience influencing architecture and standards across multiple teams without direct people management responsibility.
  • Strong understanding of data quality, observability, governance, and reliability practices in enterprise environments.
  • Adept at partnering with CloudOps, Security, IT, AI Engineering, and Data Engineering teams to ensure the cloud platform supports both current and future needs.
  • Excellent communication skills with the ability to engage both technical and non-technical stakeholders.