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Live In Data Platform Engineer Jobs in Pennsylvania

Judge Group, Inc.

Data Platform Engineer

Ridley Park, PA · On-site

$65 - $70/hr

This role combines data engineering, platform engineering, DevOps support, and business-focused ... in maintaining the DLP reference architecture across environments - Build, maintain, and validate ...

ScrumLink, Inc.

Data Platform Architect

Pittsburgh, PA · On-site

$59.50 - $76.50/hr

Bachelor's degree in Computer Science, Engineering, or a related field (Master's preferred). Skills & Technical Expertise * Data Platforms & Processing * Hadoop ecosystems, modern data lakehouse ...

Deloitte

Databricks Data Engineer II

Philadelphia, PA · On-site

$115K - $138K/yr

Practitioners collaborate across business and technology functions to solve complex challenges in data modernization, governance, platform engineering, and insight delivery. Qualifications Required:

Deloitte

Databricks Data Engineer II

Pittsburgh, PA · On-site

$111K - $133K/yr

Practitioners collaborate across business and technology functions to solve complex challenges in data modernization, governance, platform engineering, and insight delivery. Qualifications Required:

Dlapiper

Data Engineer

Philadelphia, PA

$115K - $138K/yr

Minimum Years of Experience * 3 years of experience in data engineering and/or data platform engineering (pipelines, integration, and operational support). Essential Job Expectations While the ...

1 point system

Platform Engineer

Philadelphia, PA · On-site

Job Title Platform Engineer/DevOps Engineer Client Confidential (Financial Services) Location Onsite in Cedar Rapids, Iowa / Denver Colorado / Philadelphia, PA (5 days onsite in a week) Type of Hire ...

Wolfe, LLC

VP, Data Platform and Knowledge

Pittsburgh, PA · On-site

$200K - $226K/yr

A data quality scoring system is live across all core data sources, with at least 90% of priority ... Qualifications * 10+ years of progressive experience in data platform, data engineering, or ...

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Live In Data Platform Engineer information

How much do data platform engineers make?

Data platform engineers typically earn a median salary ranging from $100,000 to $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in cloud platforms and big data tools can earn higher compensation, often exceeding $180,000 per year.

Can I make 200K as a data engineer?

A Live In Data Platform Engineer can potentially earn $200,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, data architecture, and big data tools, as well as in high-demand industries or senior roles. Compensation varies based on location, company size, and individual expertise, with senior or specialized engineers often reaching or exceeding this salary level.

What is the difference between Live In Data Platform Engineer vs Data Engineer?

AspectLive In Data Platform EngineerData Engineer
CredentialsBachelor's in CS, Data Science, or related; certifications like AWS, Azure, or GCPBachelor's in CS, IT, or related; certifications like AWS, GCP, or Hadoop
Work EnvironmentOn-site/live-in setup, often in remote or rural locations, supporting real-time data systemsOffice-based or remote, focusing on data pipeline development and management
Industry UsageUsed in industries requiring constant on-site data monitoring, such as energy or remote facilitiesCommon across tech, finance, healthcare, and other sectors for data infrastructure

The Live In Data Platform Engineer specializes in maintaining real-time data systems in on-site or remote environments, often requiring a live-in presence. In contrast, Data Engineers focus on building and managing data pipelines across various industries, typically working remotely or in-office. Both roles require similar technical skills but differ mainly in work setting and specific responsibilities.

What engineers make $300,000 a year?

Senior data platform engineers, especially those with expertise in large-scale data systems, cloud infrastructure, and advanced programming skills, can earn $300,000 or more annually. High compensation often requires extensive experience, specialized certifications, and leadership responsibilities within organizations that rely heavily on data infrastructure.

What engineer makes $500,000 a year?

A Live In Data Platform Engineer can earn $500,000 annually, especially with extensive experience, specialized skills in cloud platforms, data architecture, and high-demand environments. Such compensation often includes base salary, bonuses, and stock options in large tech companies or startups with significant data infrastructure needs.
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Live In Data Platform Engineer jobs near you
Principal Data Platform Engineer

Principal Data Platform Engineer

MedRisk LLC

Conshohocken, PA • On-site

Full-time

Posted 3 days ago

MedRisk rating

8.0

Company rating: 8.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

119th of 487 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.

What MedRisk employees say

Pay

Benefits

Hours and flexibility

Workplace

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