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Ruby On Rails Jobs in Pennsylvania (NOW HIRING)

Vanguard Group

Principal AI Engineer

Malvern, PA · On-site

You'll collaborate with senior engineers and product teams-gaining hands-on experience while contributing to real-world AI solutions. As a Principal AI Engineer, you will be a pivotal technical ...

Vanguard Group, Inc.

Principal AI Engineer

Malvern, PA · On-site

You'll collaborate with senior engineers and product teams-gaining hands-on experience while contributing to real-world AI solutions. As a Principal AI Engineer, you will be a pivotal technical ...

Vangard, Inc.

Principal AI Engineer

Malvern, PA · On-site

You'll collaborate with senior engineers and product teams-gaining hands-on experience while contributing to real-world AI solutions. As a Principal AI Engineer, you will be a pivotal technical ...

Reworld

Principal Combustion Engineer

Home, PA

Success in this role depends as much on credibility, discretion, and influence as it does on combustion expertise. The Principal Combustion Engineer acts as a trusted conduit between plant operations ...

Johnson Controls

Principal Project Engineer

York, PA · On-site

$89K - $149K/yr

Extensive product and on the job/cross training opportunities * Encouraging and collaborative team environment * Dedication to safety through our Zero Harm policy What You Will Do: The Custom Air ...

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$25.6K

$122.4K

$171.9K

How much do ruby on rails jobs pay per year?

As of Jul 15, 2026, the average yearly pay for ruby on rails in Pennsylvania is $122,407.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,700.00 and $140,800.00 per year, depending on experience, location, and employer.

What are Ruby on Rails developers?

Ruby on Rails developers are software engineers who specialize in building web applications using the Ruby on Rails framework. They use the Ruby programming language and the Rails framework to create scalable, maintainable, and efficient websites or web applications. Their responsibilities often include designing database structures, writing server-side logic, integrating front-end components, and deploying applications. Ruby on Rails developers work in a variety of industries and are valued for their ability to quickly develop robust web solutions.

Is Ruby on Rails a good career?

Ruby on Rails is a popular web development framework, and roles for Rails developers are in demand due to its use in startups and established companies. Skills in Ruby, Rails, and related tools can lead to job opportunities with competitive salaries. The career typically involves continuous learning to keep up with updates and best practices.

What Is Ruby On Rails?

Ruby on Rails is an application framework for web development. Specifically, it focuses on server-side functions and relies on the model-view-controller pattern. Rails is the framework itself, while Ruby is the programming language in which Rails is written. Ruby on Rails was designed to cut down on repetitive tasks and to be easy to learn with large, easily accessible libraries. It is open source as well, which means there is a large community that you can utilize to answer questions or improve your skills.

What are the key skills and qualifications needed to thrive as a Ruby on Rails Developer, and why are they important?

To thrive as a Ruby on Rails Developer, a solid grasp of Ruby programming, Rails framework, object-oriented design, and web development fundamentals is essential, often supported by a degree in computer science or related experience. Familiarity with version control systems like Git, databases such as PostgreSQL or MySQL, and deployment tools like Heroku or AWS is typically required. Strong problem-solving skills, attention to detail, and effective communication help developers collaborate with teams and address client needs efficiently. These skills are crucial for building robust, scalable web applications and adapting to evolving project requirements.

Is Ruby on Rails still in demand?

Ruby on Rails remains a popular web development framework, especially for startups and small to medium-sized businesses. While demand has shifted towards JavaScript frameworks and other backend technologies, many companies still seek Rails developers for maintaining and building applications, and knowledge of related tools like Git and SQL enhances employability.

What is a Ruby on Rails job?

A Ruby on Rails job involves developing and maintaining web applications using the Ruby on Rails framework. It typically requires skills in Ruby programming, front-end technologies, and understanding of databases like PostgreSQL or MySQL. The role may include tasks such as coding, debugging, testing, and collaborating with cross-functional teams.

What is the difference between Ruby On Rails vs JavaScript Developer?

AspectRuby On RailsJavaScript Developer
Required CredentialsProficiency in Ruby, Rails framework, MVC architectureProficiency in JavaScript, frameworks like React or Angular, HTML/CSS
Work EnvironmentBackend web development, server-side scriptingFrontend development, client-side scripting
Employer & Industry UsageWeb startups, SaaS companies, e-commerce platformsWeb applications, interactive websites, mobile app development

Ruby On Rails and JavaScript Developers often work together but focus on different parts of web development. Rails is primarily used for backend development with a focus on server-side logic, while JavaScript developers handle the frontend, creating interactive user interfaces. Both roles are essential in full-stack development, but their skills and tools differ significantly.

Is Ruby on Rails still used in 2026?

Ruby on Rails remains a popular web development framework for backend roles, especially for startups and companies valuing rapid development. While other frameworks like Node.js and Django have gained popularity, Rails continues to be maintained and used in production environments, with many developers working with its conventions and tools.

What are some common challenges faced by Ruby on Rails developers when working in agile teams?

Ruby on Rails developers in agile environments often encounter challenges such as rapidly adapting to changing requirements and maintaining code quality during frequent iterations. Collaborating closely with designers, product managers, and QA specialists requires clear communication and flexibility, especially when integrating new features or resolving bugs under tight deadlines. Additionally, balancing the need for quick delivery with best practices like writing tests and refactoring code can be demanding but is critical for long-term project success.
More about Ruby On Rails jobs
What are the most commonly searched types of Ruby On Rails jobs in Pennsylvania? The most popular types of Ruby On Rails jobs in Pennsylvania are:
What are popular job titles related to Ruby On Rails jobs in Pennsylvania? For Ruby On Rails jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Ruby On Rails jobs in Pennsylvania look for? The top searched job categories for Ruby On Rails jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Ruby On Rails jobs? Cities in Pennsylvania with the most Ruby On Rails job openings:
Ruby On Rails jobs near you
Infographic showing various Ruby On Rails job openings in Pennsylvania as of July 2026, with employment types broken down into 1% As Needed, 68% Full Time, 24% Part Time, 1% Temporary, 5% Contract, and 1% Nights. Highlights an 90% Physical, 5% Hybrid, and 5% Remote job distribution, with an average salary of $122,407 per year, or $58.8 per hour.
Principal Data Engineer

Principal Data Engineer

Medical Guardian

Philadelphia, PA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago

Job description

About Medical Guardian:
Medical Guardian is a fast-growing digital health and safety company on a mission to help people live a life without limits. With 13 consecutive years on the Inc. 5000 list of Fastest Growing Companies, we are redefining what it means to age confidently and independently.
We support over 625,000 members nationwide with life-saving emergency response systems and remote patient monitoring solutions. Trusted by families, healthcare providers, and care managers, our work is powered by a culture of innovation, compassion, and purpose.
Mission:
This role is focused on building and leading the data engineering foundation that powers real-time decisioning, operational applications, analytics, ML/AI model development, and data services across Medical Guardian.
The Principal Data Engineer will own the design, delivery, and maturity of production-grade data pipelines and data platforms, with a primary emphasis on real-time streaming, IoT telemetry, Databricks, Azure, data services for APIs and microservices, and reliable data products for downstream consumption.
Role Summary:
We are looking for a Principal Data Engineer to serve as a hands-on technical and people leader for data engineering, data platform architecture, real-time streaming, and production data services. This role will focus on designing, building, operating, and improving data pipelines and data products while also bringing principal-level judgment to architecture, stakeholder shaping, delivery priorities, team management, and production readiness.
This is a hands-on engineering leadership role first. The ideal candidate should be comfortable spending significant time working directly with Databricks, Spark, SQL, Python/PySpark, Azure services, streaming architectures, data quality frameworks, pipeline automation, CI/CD, and production troubleshooting. They should also be able to operate with the maturity of a principal-level leader: shaping unclear requirements, making pragmatic technical decisions, managing and mentoring engineers, and driving work forward without waiting for perfect specifications.
This is a fast-moving, startup-like environment. Requirements may be incomplete, priorities may evolve, and the right candidate will help create clarity while building quickly. We need someone who can move from ambiguous business need to reliable data capability with urgency, discipline, and ownership.
Stakeholder shaping is a critical part of this role. The Principal Data Engineer should be able to work directly with business, product, software engineering, analytics, ML/AI, operations, and leadership stakeholders to define what data needs to exist, how it should be consumed, what production guarantees are required, and how success should be measured.
A background in commercial software, SaaS, digital products, healthtech, fintech, IoT, data platforms, or other product-driven environments is strongly preferred. We want someone who understands that data pipelines and data services are not just technical artifacts. They are product capabilities that support real users, real workflows, operational decisions, ML/AI systems, APIs, analytics, and measurable business outcomes.
Key Responsibilities:
Hands-On Data Engineering and Platform Development
  • Design, build, optimize, and operate production-grade batch and streaming data pipelines on Azure and Databricks, with a primary focus on real-time IoT and telemetry use cases within a Medallion architecture.
  • Develop ETL/ELT workflows to ingest, transform, validate, and serve large volumes of structured, semi-structured, unstructured, and streaming data.
  • Build and maintain reliable data products, data services, APIs, and microservices that support operational applications, analytics, software engineering, and ML/AI teams.
  • Use Python, PySpark, Spark SQL, SQL, Delta Lake, Databricks Workflows, CI/CD, and related tools to build maintainable, testable, and observable data systems.
  • Troubleshoot complex production pipeline issues across Databricks, Azure, streaming systems, APIs, and source systems, including root cause analysis, corrective action, and prevention planning.
  • Move quickly from rough business need to prototype, pilot, and production-ready data capability while maintaining appropriate engineering discipline.

Real-Time Streaming, IoT Telemetry, and Operational Data Services
  • Lead the design and delivery of real-time streaming ingestion and processing patterns for connected medical device telemetry, event data, and operational data feeds.
  • Implement streaming solutions using Azure Event Hubs, Azure Stream Analytics, Databricks, Delta Lake, and related Azure integration patterns.
  • Design cost-effective throughput, partitioning, delivery, retention, and replay strategies for high-volume event and telemetry workloads.
  • Create consumption patterns that support APIs, microservices, operational applications, near-real-time decisioning, analytics, and ML/AI use cases.
  • Define reliability, latency, quality, observability, and supportability expectations for production streaming systems.

Databricks, Lakehouse, and Data Platform Architecture
  • Set direction for Databricks-based data engineering patterns, including Medallion architecture, Delta Lake, Spark optimization, data modeling, data quality, and reusable pipeline design.
  • Optimize production Databricks pipelines using PySpark, Spark SQL, Delta Lake, partitioning strategies, caching, shuffle optimization, cluster/job configuration, and cost-aware design.
  • Establish practical standards for pipeline structure, code organization, testing, deployment, monitoring, documentation, and ownership.
  • Partner with data platform, security, infrastructure, and engineering teams to ensure the data platform is scalable, secure, reliable, and aligned with enterprise architecture.
  • Make pragmatic architecture tradeoffs between speed, durability, cost, governance, performance, and downstream business impact.

Stakeholder Shaping and Cross-Functional Partnership
  • Work directly with business, product, analytics, ML/AI, operations, software engineering, and leadership stakeholders to clarify what data is needed, why it matters, how it will be used, and what success looks like.
  • Translate ambiguous business needs into concrete data requirements, data product definitions, architecture options, delivery priorities, and implementation plans.
  • Ask practical questions early: who will use the data, what decision or workflow does it support, what latency and quality are required, what happens if the data is wrong or late, and how will we know the capability is creating value?
  • Help the organization avoid becoming a data ticket factory by shaping solutions, not just executing requests.
  • Communicate architecture decisions, tradeoffs, risks, dependencies, and delivery options clearly to technical and non-technical stakeholders.

Team Management and Principal-Level Technical Leadership
  • Manage, mentor, and develop data engineers, providing clear expectations, technical guidance, prioritization support, feedback, and accountability.
  • Provide technical leadership through hands-on example, strong engineering judgment, clear recommendations, and pragmatic decision-making.
  • Lead design reviews, code reviews, production readiness reviews, incident reviews, and architecture discussions across data engineering initiatives.
  • Establish and improve engineering standards for data quality, testing, CI/CD, observability, documentation, runbooks, cost management, privacy, and security.
  • Proactively identify platform risks, data gaps, unclear ownership, operational weaknesses, and opportunities to improve reliability, scalability, and delivery speed.
  • Influence without relying only on formal authority by building trust, framing tradeoffs, and helping cross-functional teams get to decisions.

ML/AI, Analytics, and GenAI Enablement
  • Partner with ML engineers, data scientists, analytics engineers, and analysts to deliver reliable data pipelines, feature pipelines, training datasets, scoring inputs, and feedback loops.
  • Support the data foundation for predictive models, risk scores, operational decisioning, GenAI workflows, RAG, document intelligence, summarization, and AI-enabled automation.
  • Help define data contracts, model-ready datasets, feature definitions, lineage, and monitoring expectations for ML/AI and analytics use cases.
  • Ensure downstream consumers understand the meaning, freshness, quality, limitations, and appropriate use of the data products they depend on.

Governance, Data Quality, Security, and Production Operations
  • Apply privacy-first, security-aware, and governance-aligned practices for regulated, sensitive, and operationally critical data.
  • Design and implement data quality checks, validation rules, anomaly detection, schema expectations, alerting, and operational monitoring.
  • Ensure production pipelines and services are supportable, observable, documented, recoverable, and aligned with business continuity needs.
  • Drive incident response and continuous improvement for data platform and pipeline issues, including root cause analysis and preventative remediation.
  • Balance innovation with reliability, compliance, privacy, cost discipline, and operational usefulness.

Required Qualifications:
  • 10+ years of professional experience in data engineering, software engineering, data platform engineering, distributed systems, analytics engineering, or related technical fields.
  • 7+ years of hands-on experience designing, building, optimizing, and operating production data pipelines, data platforms, or data services.
  • 5+ years of hands-on experience with modern cloud data platforms, including Databricks, Spark, Delta Lake, SQL, Python/PySpark, and production pipeline orchestration.
  • 3+ years of experience leading, managing, mentoring, or providing technical direction to data engineers or related technical teams.
  • Strong experience with Azure cloud services for data engineering, streaming, integration, storage, security, and production operations.
  • Experience designing and operating real-time streaming, event-driven, or near-real-time data pipelines in production or business-critical environments.
  • Experience applying DevOps, CI/CD, testing, version control, code review, documentation, and automation practices to data engineering workloads.
  • Experience building data services, APIs, microservices, or reusable consumption patterns for downstream applications, analytics, ML/AI, or operational workflows.
  • Strong understanding of data quality, observability, monitoring, lineage, reliability, cost optimization, privacy, and production support for data systems.
  • Experience translating ambiguous business needs into technical designs, architecture recommendations, delivery plans, and measurable outcomes.
  • Ability to explain data architecture, pipeline behavior, tradeoffs, assumptions, risks, and limitations to both technical and non-technical stakeholders.
  • Strong ownership mindset and ability to drive work forward independently in a fast-moving, evolving environment.

Preferred Qualifications:
  • 12+ years of relevant professional experience in data engineering, software engineering, data platforms, distributed systems, analytics engineering, commercial software, or production data products.
  • Experience working as a principal, staff, lead, manager, or architect-level data engineering leader in a production environment.
  • Experience managing direct reports, setting team priorities, developing engineers, and improving team execution and accountability.
  • Experience working in commercial software, SaaS, digital products, healthtech, fintech, IoT, consumer technology, or other product-driven environments.
  • Experience in startup, scale-up, innovation, new product development, or rapid-build environments where the candidate had to operate with ambiguity and drive work forward independently.
  • Experience with Azure Event Hubs, Azure Stream Analytics, Azure Service Bus, Azure Data Factory, Azure Functions, ADLS, Azure Cosmos DB, Event Grid, or similar Azure services.
  • Experience with medical device telemetry, IoT data, remote patient monitoring, healthcare operations, regulated data, HIPAA-sensitive environments, or safety-critical workflows.
  • Experience building data platforms or data products that support APIs, microservices, operational applications, ML/AI systems, GenAI workflows, RAG, analytics, and executive reporting.
  • Experience with data contracts, semantic layers, feature stores, model-ready datasets, data lineage, schema evolution, CDC, and operational feedback loops.
  • Experience with performance tuning, cost optimization, FinOps practices, data platform reliability, and production incident management.
  • Experience partnering with product managers, software engineers, ML engineers, analysts, business leaders, and operations teams to turn data into usable business capabilities.
  • Experience building MVPs, validating assumptions, iterating based on feedback, and maturing prototypes into durable production systems.

Benefits
  • Health Care Plan (Medical, Dental & Vision)
  • Paid Time Off (Vacation, Sick Time Off & Holidays)
  • Company Paid Short Term Disability and Life Insurance
  • Retirement Plan (401k) with Company Match

Apply