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Remote Observability Engineer Jobs in Philadelphia, PA

Engineering Leadership and Team Development * Lead, manage, and develop the PracticeMatch ... Experience designing and operating CI/CD pipelines, automated test frameworks, and observability ...

Leading enterprises use our unified security and observability platform to keep their digital ... DevOps, security, business applications, and/or analytics. Subscription, SaaS, or Cloud software ...

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Remote Observability Engineer information

See Philadelphia, PA salary details

$38.3K

$116.9K

$193.2K

How much do remote observability engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for remote observability engineer in Philadelphia, PA is $116,917.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,800.00 and $152,900.00 per year, depending on experience, location, and employer.

What is a remote observability engineer?

A Remote Observability Engineer is a professional responsible for designing, implementing, and maintaining systems that monitor the health, performance, and reliability of software applications and infrastructure from a remote location. They use observability tools to collect and analyze logs, metrics, and traces, helping organizations quickly detect and resolve issues. Their work ensures that distributed systems are transparent, reliable, and efficient, often collaborating with development, operations, and security teams. Remote Observability Engineers often work from anywhere, leveraging cloud-based tools and platforms to manage complex IT environments.

What are the typical collaboration patterns for a remote observability engineer working with distributed teams?

Remote Observability Engineers frequently collaborate with software developers, DevOps teams, and IT operations to ensure systems are monitored effectively and issues are detected early. Working remotely, you'll often use communication tools like Slack, Jira, and video conferencing to coordinate incident response, discuss monitoring strategies, and review system health dashboards. Regular sync meetings and asynchronous updates are common, and you'll likely contribute to documentation and knowledge sharing to keep all stakeholders informed. Building strong communication habits is important, as much of the troubleshooting and improvement work hinges on clear coordination with multiple teams.

What are the key skills and qualifications needed to thrive as a remote observability engineer, and why are they important?

To thrive as a Remote Observability Engineer, you need strong expertise in monitoring, logging, and tracing systems, along with a background in computer science or related technical fields. Familiarity with tools like Prometheus, Grafana, ELK Stack, Datadog, and cloud platforms is typically required, as well as relevant certifications such as AWS Certified Cloud Practitioner or Google Cloud Professional DevOps Engineer. Excellent problem-solving abilities, communication skills, and a proactive mindset help you detect and resolve issues before they impact users. These competencies ensure system reliability, enable rapid incident response, and support seamless collaboration in distributed environments.

What is the difference between Remote Observability Engineer vs Site Reliability Engineer?

AspectRemote Observability EngineerSite Reliability Engineer
CredentialsKnowledge of monitoring tools, scripting, cloud platformsSame as Observability Engineer, plus SRE certifications often preferred
Work EnvironmentFocus on monitoring, logging, and tracing systems remotelyBroader scope including system reliability, incident response, and automation
Industry UsagePrimarily in tech, SaaS, cloud servicesWidely in tech, finance, and large-scale online services

The Remote Observability Engineer specializes in monitoring and analyzing system performance remotely, focusing on tools like logs and metrics. In contrast, the Site Reliability Engineer has a broader role, ensuring overall system reliability, automation, and incident management. While both roles require similar technical skills, SREs often have additional responsibilities related to system resilience and scalability.

What are the most commonly searched types of Observability Engineer jobs in Philadelphia, PA?

The most popular types of Observability Engineer jobs in Philadelphia, PA are:

What are popular job titles related to Remote Observability Engineer jobs in Philadelphia, PA?

For Remote Observability Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Remote Observability Engineer jobs in Philadelphia, PA look for?

The top searched job categories for Remote Observability Engineer jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Remote Observability Engineer jobs?

Cities near Philadelphia, PA with the most Remote Observability Engineer job openings:

Principal Data Engineer - Safety Analytics (Global Medical Safety)

Jj

Titusville, NJ • On-site, Remote

Full-time

Retirement, PTO

Re-posted 19 days ago


Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Engineering

Job Category:

Scientific/Technology

All Job Posting Locations:

Horsham, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

About Innovative Medicine

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Learn more at https://www.jnj.com/innovative-medicine

Prefered Location:

Horsham, PA or Titusville, NJ. Remote work will considered on a case by case basis.

Role Overview

We are seeking a Principal Data Engineer to provide technical leadership within Global Medical Safety (GMS), supporting the Safety Analytics organization. This role is focused on building and enabling modern safety analytics tools using AI, Machine Learning, and GenAI, underpinned by robust, compliant, and scalable data engineering on Google Cloud Platform (GCP).

The Principal Data Engineer is responsible for end-to-end ownership of safety analytics data engineering, spanning data intake, data quality and continuity, pipeline and architecture design, automation, performance optimization, and compliance. The role enables advanced analytical, machine learning, and predictive capabilities for pharmacovigilance and serves as a technical data engineering leader within Global Medical Safety.

This is a Principal-level individual contributor role with broad technical influence, working closely with safety scientists, analytics teams, data scientists, IT, and platform partners to deliver trusted, production-grade analytics capabilities for safety decision-making.

Key Responsibilities

Safety Analytics & Pharmacovigilance Enablement

  • Design and maintain production-grade data pipelines and curated datasets that directly support pharmacovigilance activities, including safety monitoring, analytics, and regulatory reporting.

  • Ensure data engineering solutions produce reproducible, explainable, and trusted analytics outputs suitable for safety decision support and inspection readiness.

  • Enable AI/ML and GenAI workflows for safety analytics, including:

  • Feature engineering and feature store enablement
  • Embeddings, vectorized representations, and semantic retrieval
  • Retrieval-Augmented Generation (RAG) patterns for safety analytics tools

End-to-End Data Architecture & Lifecycle Ownership

  • Own the end-to-end data lifecycle for safety analytics, from source system intake through transformation, serving, and downstream analytical consumption, ensuring data continuity, traceability, and integrity.

  • Lead architectural decisions across ingestion, transformation, storage, and serving layers on GCP (e.g., BigQuery, Dataform, object storage).

  • Design, implement, and automate scalable, reusable data pipelines and architectures to support evolving safety analytics needs.

Data Quality, Governance & Compliance

  • Establish and enforce data quality, validation, lineage, and observability standards for safety analytics datasets.

  • Define and implement data governance practices, including data contracts, schema versioning, access control, stewardship, and lifecycle management.

  • Ensure safety analytics data and systems meet Global Medical Safety requirements for reliability, auditability, and regulatory use.

GxP Validation & Regulatory Readiness

  • Apply GxP validation expertise to data pipelines, analytics services, and supporting infrastructure.

  • Partner with quality and compliance teams to implement CSV/CSA-aligned controls, audit trails, documentation, and organizational change.

  • Balance delivery velocity and innovation with the rigor required for regulated pharmacovigilance systems.

Services, APIs & Microservices

  • Design and build APIs and microservices-based architectures to operationalize safety analytics and ML capabilities (e.g., feature serving, retrieval services, analytics backends).

  • Deploy and operate services on GCP (e.g., Cloud Run, GKE) with a strong focus on security, scalability, and observability.

  • Enforce contract-first integration patterns between producing and consuming systems to ensure reliability and safe evolution.

Infrastructure, CI/CD & Cost Optimization

  • Provision and manage cloud infrastructure using Terraform (Infrastructure as Code) on GCP.

  • Build and maintain CI/CD pipelines (e.g., Jenkins) for data pipelines, analytics services, feature pipelines, and ML data assets.

  • Continuously optimize the performance and cost efficiency of data and analytics infrastructure while maintaining compliance and reliability standards.

Technical Leadership & Stakeholder Engagement

  • Serve as a technical authority and data engineering leader for Safety Analytics within Global Medical Safety.

  • Review and influence designs across pipelines, services, feature stores, and AI/ML integrations to maintain a high technical bar. Collaborate closely with safety scientists, epidemiologists, biostatisticians, analytics teams, IT, and platform partners to translate safety needs into scalable technical solutions.

  • Communicate complex technical concepts and tradeoffs clearly to both technical and non-technical stakeholders.

  • Enable and upskill teams through mentorship, guidance, and knowledge sharing on modern data, cloud, and AI technologies.

Qualifications

  • Master's degree in Computer Science, Engineering, or a related field (or equivalent experience) is required.

  • 5+ years of experience in data engineering or analytics engineering with increasing responsibilities.

  • Proficient programming skills in Python and SQL.

  • Deep understanding of data architecture for analytics and ML (e.g., batch/streaming, modeling, performance optimization).

  • Proven ability to translate complex problems into clear, concise, and testable programming code/tools.

  • Experience implementing data contracts, data validation, schema versioning, and governance practices, as well as a solid understanding of leading cloud concepts (GCP preferred).

  • Experience designing and operating APIs and microservices-based architectures.

  • Excellent written and verbal communication, customer service, interpersonal, and teamwork skills to foster a collaborative team environment.

  • Solid understanding of SDLC and Agile methodologies, alongside basic project management skills.

  • Experience building production workloads on Google Cloud Platform (GCP) is preferred.

  • Experience provisioning infrastructure using Terraform (Infrastructure as Code) and building CI/CD pipelines (e.g., Jenkins) is preferred.

  • Experience in pharmaceuticals, life sciences, healthcare, or a related regulated domain is preferred.

  • GCP certification is preferred.

  • Experience enabling AI/ML and GenAI workflows (e.g., feature engineering, RAG patterns, semantic retrieval) for analytical applications is preferred.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.


Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, external applicants please
contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your
accommodation resource.

#JNJTech

#LI-Hybrid

#LI-GR1

Required Skills:

Preferred Skills:

Advanced Analytics, Agility Jumps, Coaching, Critical Thinking, Data Engineering, Data Governance, Data Modeling, Data Privacy Standards, Data Science, Digital Fluency, Execution Focus, Hybrid Clouds, Organizing, Presentation Design, Technical Development, Technical Writing, Technologically Savvy

The anticipated base pay range for this position is :

$102,000.00 - $177,100.00

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company's
consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation -120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado -48 hours per calendar year; for employees who reside in the State of Washington -56 hours per calendar year
Holiday pay, including Floating Holidays -13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave - 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave - 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave - 80 hours in a 52-week rolling period10 days
Volunteer Leave - 32 hours per calendar year
Military Spouse Time-Off - 80 hours per calendar year
For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits