📍 Job Overview

Job Title: Observability Platform Engineer
Company: G-Research
Location: Dallas, Texas, United States
Job Type: Hybrid
Category: DevOps Engineer
Date Posted: 2025-07-31
Experience Level: 5-10 years
Remote Status: On-site/Hybrid

🚀 Role Summary

Key web technology aspect 1: Manage critical entry and exit points to telemetry services, ensuring reliable production and consumption of telemetry data for services.
Key web technology aspect 2: Design and implement robust, scalable data pipelines that ingest, route, and visualize telemetry data, empowering engineers to gain actionable insights into their systems.
Key web technology aspect 3: Collaborate with cross-functional engineering teams to establish observability as a core function of the development lifecycle and integrate observability systems with application teams.
Key web technology aspect 4: Enable SRE frameworks, promote SLAs, SLOs, and SLIs, and work closely with platform teams to ensure reliability is constantly improving.

📝 Enhancement Note: This role requires a strong understanding of observability stacks and the unique challenges associated with managing telemetry at cloud-scale volumes. Familiarity with core Site Reliability Engineering (SRE) principles is highly beneficial.

💻 Primary Responsibilities

Web technology responsibility 1: Be a key contributor to the development of observability and reliability platforms, contributing to the roadmap for observability tooling, and ensuring alignment with business goals and scalability requirements.
Web technology responsibility 2: Work with telemetry data at enormous scale, ingesting data from industry-leading GPU clusters, and ensure seamless integration with AWS services.
Web technology responsibility 3: Collaborate with cross-functional engineering teams to establish observability as a core function of the development lifecycle and ensure observability systems are fully integrated and providing necessary insights.
Web technology responsibility 4: Enable SRE frameworks, promote SLAs, SLOs, and SLIs, and work closely with platform teams to ensure reliability is constantly improving.
Web technology responsibility 5: Help foster a culture of continuous learning and improvement, encouraging adoption of new observability tools and techniques.

📝 Enhancement Note: The primary responsibilities of this role revolve around managing and enhancing the reliability of the entire High-Performance Computing (HPC) stack, from networking and storage through to compute and application platforms.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience may be considered in lieu of a degree.

Experience: Proven experience on observability or SRE teams in a cloud-native or hybrid-cloud environment, running platforms in production and at scale.

Required Skills:

Proven expertise in reliability engineering concepts, including different types of testing, progressive deployments, error budgets, the role observability plays, and fault-tolerant design.
Hands-on experience with modern observability tools and frameworks such as Prometheus, OTEL (OpenTelemetry), Grafana, and enterprise SaaS Observability platforms, such as Datadog and Dynatrace.
Expertise in designing, building, and scaling observability solutions for distributed systems.
Customer-focused mindset, with an enthusiasm for providing infrastructure as a service and defaulting to a product lens when evaluating platform scale problems.
Excellent communication skills and the ability to collaborate with cross-functional teams.
Experience with cloud platforms, such as AWS, Azure, or Google Cloud.
Familiarity with microservices architecture and containerized environments, such as Kubernetes and Docker.
Knowledge of infrastructure as code (IaC) and automation tools, such as Terraform and Ansible.

Preferred Skills:

Experience with large-scale observability platforms for a diverse customer base.
Familiarity with core Site Reliability Engineering (SRE) principles.

📝 Enhancement Note: The required and preferred skills for this role emphasize a strong background in observability and SRE, with a focus on cloud-native environments and distributed systems.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Portfolio requirement 1: Demonstrate experience managing and enhancing the reliability of High-Performance Computing (HPC) stacks, from networking and storage through to compute and application platforms.
Portfolio requirement 2: Showcase your ability to design and implement robust, scalable data pipelines that ingest, route, and visualize telemetry data for services.
Portfolio requirement 3: Highlight your experience collaborating with cross-functional engineering teams to establish observability as a core function of the development lifecycle and integrate observability systems with application teams.
Portfolio requirement 4: Display your expertise in enabling SRE frameworks, promoting SLAs, SLOs, and SLIs, and working closely with platform teams to ensure reliability is constantly improving.

Technical Documentation:

Technical documentation requirement 1: Provide code quality, commenting, and documentation standards for observability and reliability platforms.
Technical documentation requirement 2: Demonstrate version control, deployment processes, and server configuration for observability and reliability platforms.
Technical documentation requirement 3: Showcase testing methodologies, performance metrics, and optimization techniques for observability and reliability platforms.

📝 Enhancement Note: The portfolio requirements for this role focus on demonstrating expertise in managing and enhancing the reliability of HPC stacks, with a strong emphasis on observability and SRE.

💵 Compensation & Benefits

Salary Range: $150,000 - $200,000 per year (based on market research for similar roles in the Dallas, TX area)

Benefits:

Market-leading compensation plus annual discretionary bonus
Lunch provided in the office (via GrubHub)
Informal dress code and excellent work/life balance
Excellent paid time off allowance of 25 days
Sick days, military leave, and family and medical leave
Generous 401(k) plan
16-weeks’ fully paid parental leave
Medical and Prescription, Dental, and Vision insurance
Life and Accidental Death & Dismemberment (AD&D) insurance
Employee Assistance and Wellness programs
Generous relocation allowance and support
Great selection of office snacks, and hot and cold drinks
Free on-site gym and car parking

Working Hours: Full-time, with a hybrid work arrangement (2-3 days in the office per week)

📝 Enhancement Note: The salary range for this role is estimated based on market research for similar roles in the Dallas, TX area, with regional adjustments for cost of living. The benefits listed are specific to G-Research and may vary for other employers.

🎯 Team & Company Context

Company Culture:

Industry: Quantitative research and technology firm
Company Size: Medium (250-999 employees)
Founded: 2005 (19 years ago)
Team Structure: The Observability Platform team operates under the broader Platform Engineering department and collaborates with cross-functional engineering teams to establish observability as a core function of the development lifecycle.

Development Methodology:

Agile/Scrum methodologies and sprint planning for web projects
Code review, testing, and quality assurance practices
Deployment strategies, CI/CD pipelines, and server management

Company Website: G-Research

📝 Enhancement Note: G-Research is a leading quantitative research and technology firm with offices in London and Dallas. The company employs some of the best people in their field and nurtures their talent in a dynamic, flexible, and highly stimulating culture where world-beating ideas are cultivated and rewarded.

📈 Career & Growth Analysis

Web Technology Career Level: Senior DevOps Engineer / Site Reliability Engineer

Reporting Structure: The Observability Platform Engineer will report to the Observability Platform Team Lead and collaborate with cross-functional engineering teams.

Technical Impact: This role has a significant impact on the reliability and performance of G-Research's High-Performance Computing (HPC) stack, ensuring that engineers across the business can reliably produce and consume telemetry data for their services.

Growth Opportunities:

Growth opportunity 1: Develop expertise in observability and reliability platforms, with the potential to take on a technical leadership role within the team or across the broader Platform Engineering department.
Growth opportunity 2: Gain experience with emerging technologies in a cutting-edge environment, working on the latest tools and frameworks in observability and SRE.
Growth opportunity 3: Contribute to the development of G-Research's observability and reliability platforms, driving innovation and improvement in the field of quantitative research and technology.

📝 Enhancement Note: The career growth opportunities for this role focus on developing expertise in observability and reliability platforms, with the potential to take on technical leadership roles and contribute to the development of cutting-edge technologies in the field of quantitative research and technology.

🌐 Work Environment

Office Type: Hybrid work environment with 2-3 days in the office per week.

Office Location(s): Dallas, Texas, United States

Workspace Context:

Workspace aspect 1: Collaborative work environment with cross-functional teams, fostering knowledge sharing and continuous learning.
Workspace aspect 2: Access to modern development tools, multiple monitors, and testing devices to ensure optimal performance and reliability of observability and reliability platforms.
Workspace aspect 3: Opportunities for cross-functional collaboration with designers, marketers, and other stakeholders to ensure observability systems are fully integrated and providing necessary insights.

Work Schedule: Full-time, with a hybrid work arrangement (2-3 days in the office per week)

📝 Enhancement Note: The work environment for this role is a hybrid work environment with 2-3 days in the office per week, providing opportunities for collaboration and knowledge sharing with cross-functional teams.

📄 Application & Technical Interview Process

Interview Process:

Process step 1: Technical preparation recommendations and coding/configuration assessment focus on observability and reliability platforms, with an emphasis on cloud-native environments and distributed systems.
Process step 2: Web architecture expectations and system design discussion, focusing on the unique challenges associated with managing telemetry at cloud-scale volumes.
Process step 3: Web development team interaction and cultural fit assessment, ensuring a strong understanding of G-Research's culture and values.
Process step 4: Final evaluation criteria and technical impact discussion, focusing on the candidate's ability to drive innovation and improvement in the field of quantitative research and technology.

Portfolio Review Tips:

Portfolio tip 1: Highlight your experience managing and enhancing the reliability of High-Performance Computing (HPC) stacks, with a focus on observability and SRE.
Portfolio tip 2: Showcase your ability to design and implement robust, scalable data pipelines that ingest, route, and visualize telemetry data for services.
Portfolio tip 3: Demonstrate your expertise in enabling SRE frameworks, promoting SLAs, SLOs, and SLIs, and working closely with platform teams to ensure reliability is constantly improving.
Portfolio tip 4: Highlight your experience collaborating with cross-functional engineering teams to establish observability as a core function of the development lifecycle and integrate observability systems with application teams.

Technical Challenge Preparation:

Challenge preparation 1: Familiarize yourself with the latest tools and frameworks in observability and SRE, with a focus on cloud-native environments and distributed systems.
Challenge preparation 2: Brush up on your knowledge of reliability engineering concepts, including different types of testing, progressive deployments, error budgets, the role observability plays, and fault-tolerant design.
Challenge preparation 3: Prepare for technical questions related to web architecture, system design, and problem-solving, with a focus on the unique challenges associated with managing telemetry at cloud-scale volumes.

📝 Enhancement Note: The interview process for this role focuses on assessing the candidate's expertise in observability and reliability platforms, with a strong emphasis on cloud-native environments and distributed systems.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies:

Not applicable for this role

Backend & Server Technologies:

AWS Services (Seamless integration with the observability platform)
Kubernetes (Containerized environments)
Docker (Containerized environments)
Terraform (Infrastructure as code)
Ansible (Automation tools)

Development & DevOps Tools:

Prometheus (Monitoring and alerting toolkit)
OTEL (OpenTelemetry) (Open-source observability framework)
Grafana (Visualization and dashboarding platform)
Datadog and Dynatrace (Enterprise SaaS Observability platforms)

📝 Enhancement Note: The technology stack for this role is focused on backend and server technologies, with an emphasis on cloud-native environments and distributed systems. The development and DevOps tools listed are essential for managing and enhancing the reliability of G-Research's High-Performance Computing (HPC) stack.

👥 Team Culture & Values

Web Development Values:

Web development value 1: Customer-focused mindset, with an enthusiasm for providing infrastructure as a service and defaulting to a product lens when evaluating platform scale problems.
Web development value 2: Continuous learning and improvement, encouraging adoption of new observability tools and techniques.
Web development value 3: Collaboration and knowledge sharing, fostering a culture of cross-functional teamwork and mutual support.
Web development value 4: Reliability and performance, ensuring that observability and reliability platforms are constantly improving and driving innovation in the field of quantitative research and technology.

Collaboration Style:

Collaboration approach 1: Cross-functional integration between developers, designers, and stakeholders, ensuring observability systems are fully integrated and providing necessary insights.
Collaboration approach 2: Code review culture and peer programming practices, fostering knowledge sharing and continuous learning.
Collaboration approach 3: Knowledge sharing, technical mentoring, and continuous learning, driving innovation and improvement in the field of quantitative research and technology.

📝 Enhancement Note: The web development values and collaboration style for this role emphasize a customer-focused mindset, continuous learning and improvement, and collaboration and knowledge sharing, fostering a culture of cross-functional teamwork and mutual support.

⚡ Challenges & Growth Opportunities

Technical Challenges:

Web development challenge 1: Managing and enhancing the reliability of High-Performance Computing (HPC) stacks, with a focus on observability and SRE.
Web development challenge 2: Designing and implementing robust, scalable data pipelines that ingest, route, and visualize telemetry data for services, with a focus on cloud-native environments and distributed systems.
Web development challenge 3: Enabling SRE frameworks, promoting SLAs, SLOs, and SLIs, and working closely with platform teams to ensure reliability is constantly improving.
Web development challenge 4: Collaborating with cross-functional engineering teams to establish observability as a core function of the development lifecycle and integrate observability systems with application teams.

Learning & Development Opportunities:

Learning opportunity 1: Develop expertise in observability and reliability platforms, with the potential to take on a technical leadership role within the team or across the broader Platform Engineering department.
Learning opportunity 2: Gain experience with emerging technologies in a cutting-edge environment, working on the latest tools and frameworks in observability and SRE.
Learning opportunity 3: Contribute to the development of G-Research's observability and reliability platforms, driving innovation and improvement in the field of quantitative research and technology.

📝 Enhancement Note: The technical challenges and learning opportunities for this role focus on developing expertise in observability and reliability platforms, with the potential to take on technical leadership roles and contribute to the development of cutting-edge technologies in the field of quantitative research and technology.

💡 Interview Preparation

Technical Questions:

Technical question 1: Describe your experience managing and enhancing the reliability of High-Performance Computing (HPC) stacks, with a focus on observability and SRE.
Technical question 2: How have you designed and implemented robust, scalable data pipelines that ingest, route, and visualize telemetry data for services, with a focus on cloud-native environments and distributed systems?
Technical question 3: Explain your approach to enabling SRE frameworks, promoting SLAs, SLOs, and SLIs, and working closely with platform teams to ensure reliability is constantly improving.

Company & Culture Questions:

Technical question 4: How do you ensure that observability systems are fully integrated and providing necessary insights, working closely with application teams and other stakeholders?
Technical question 5: Describe your experience with Agile practices and collaboration with cross-functional teams to establish observability as a core function of the development lifecycle.
Technical question 6: How do you approach continuous learning and improvement, encouraging adoption of new observability tools and techniques?

Portfolio Presentation Strategy:

Presentation strategy 1: Highlight your experience managing and enhancing the reliability of High-Performance Computing (HPC) stacks, with a focus on observability and SRE.
Presentation strategy 2: Showcase your ability to design and implement robust, scalable data pipelines that ingest, route, and visualize telemetry data for services, with a focus on cloud-native environments and distributed systems.
Presentation strategy 3: Demonstrate your expertise in enabling SRE frameworks, promoting SLAs, SLOs, and SLIs, and working closely with platform teams to ensure reliability is constantly improving.

📝 Enhancement Note: The technical questions and portfolio presentation strategy for this role focus on assessing the candidate's expertise in observability and reliability platforms, with a strong emphasis on cloud-native environments and distributed systems.

📌 Application Steps

To apply for this Observability Platform Engineer position:

Submit your application through the application link provided.
Customize your resume and portfolio to highlight your experience in observability and reliability platforms, with a focus on cloud-native environments and distributed systems.
Prepare for technical interviews by brushing up on your knowledge of reliability engineering concepts, web architecture, and system design, with a focus on the unique challenges associated with managing telemetry at cloud-scale volumes.
Research G-Research's culture and values, ensuring a strong understanding of the company's mission and commitment to quantitative research and technology.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Observability Platform Engineer