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Remote Observability Engineer Jobs in Phoenix, AZ

Koantek

Databricks Platform Architect

Chandler, AZ · Remote

Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead ... Pipeline Engineering: Design distributed processing frameworks, control flows, and configuration ...

JDA

Principal Data Platform Engineer

Scottsdale, AZ · Remote

US Remote (Preference given to Dallas, TX or Scottsdale, AZ candidates) Synonymous Business Title ... Establish monitoring, alerting, and observability across the estate, including performance ...

RevStar

Software Development Lead

Phoenix, AZ · Remote

Remote (US-Based / Eastern or Central Time Zone Preferred) * Employment Type: Full-Time W2 Are you ... Establish, document, and enforce modern engineering standards for ReactJS, NodeJS, and AWS cloud ...

RevStar

Software Development Lead

Phoenix, AZ · Remote

Remote (US-Based / Eastern or Central Time Zone Preferred) * Employment Type: Full-Time W2 Are you ... Establish, document, and enforce modern engineering standards for ReactJS, NodeJS, and AWS cloud ...

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All JobsObservability Engineer JobsRemote Observability Engineer JobsRemote Observability Engineer Jobs in Phoenix, AZ

Remote Observability Engineer information

See Phoenix, AZ salary details

$37.7K

$115K

$190.1K

How much do remote observability engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for remote observability engineer in Phoenix, AZ is $115,043.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,400.00 and $150,400.00 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 Phoenix, AZ?

The most popular types of Observability Engineer jobs in Phoenix, AZ are:

What are popular job titles related to Remote Observability Engineer jobs in Phoenix, AZ?

For Remote Observability Engineer jobs in Phoenix, AZ, the most frequently searched job titles are:

What job categories do people searching Remote Observability Engineer jobs in Phoenix, AZ look for?

The top searched job categories for Remote Observability Engineer jobs in Phoenix, AZ are:

Remote Observability Engineer jobs near you
Infographic showing various Remote Observability Engineer job openings in Phoenix, AZ as of August 2026, with employment types broken down into 90% Full Time, 6% Part Time, and 4% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $115,043 per year, or $55.3 per hour.

Databricks Platform Architect

Koantek

Chandler, AZ • Remote

Contractor

Re-posted 24 days ago

Job description

Job Title: Lead Data Platform Architect / Data bricks Migration Lead Location: Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead Data Platform Architect / Migration Specialist to spearhead the modernization of our core enterprise financial and tax allocation engines. In this role, you will lead the architectural design, definition of migration strategies, and hands-on implementation to transition large-scale legacy relational database systems (SQL Server/T-SQL) into a modern, cloud-native Databricks Lakehouse platform. The ideal candidate will have extensive experience in high-throughput distributed systems, Databricks compute optimization, performance tuning, and complex pipeline orchestration.

Key Responsibilities Architecture & Strategy: Validate, refine, and own the target architecture on Databricks. Define robust migration strategies and production-ready reference patterns to convert 150+ complex stored procedures into PySpark and Structured/Declarative Pipelines (SDP). Pipeline Engineering: Design distributed processing frameworks, control flows, and configuration-driven parameter handling for both full and incremental recalculation modes.

Performance Optimization: Address performance deltas between small and large workloads. Architect and implement acceleration techniques such as caching, partition pruning, cluster sizing, and offline/pre-calculation strategies to maintain sub-30-second user-facing reporting SLAs. Orchestration & Observability: Design and deploy enterprise-level pipeline orchestration using tools like Apache Airflow or Databricks Workflows.

Integrate robust logging, error handling, and observability patterns into existing enterprise monitoring frameworks. Governance & Security: Implement data governance models, data lineage, and schema evolution utilizing tools like Unity Catalog. AI-Assisted Delivery & Code Quality: Establish best practices for AI-assisted code generation (e.g., using Claude or advanced LLMs), providing code-review patterns and refactoring frameworks to ensure maintainable and performant output

Team Enablement: Lead code walkthroughs, design reviews, and pair-programming sessions with the development team to accelerate knowledge transfer and technical excellence. Required Technical Skills & Qualifications Core Big Data Platform: Deep expert-level knowledge of Databricks (Lakehouse architecture, Delta Lake, Unity Catalog) and Apache Spark / PySpark. Legacy Database Expertise: Strong background in relational databases, with advanced proficiency in SQL Server, T-SQL, and Stored Procedures.

Ability to reverse-engineer and refactor legacy database logic into distributed paradigms. Orchestration Tools: Hands-on experience with Apache Airflow or similar modern workflow orchestrators. Performance Tuning: Proven track record in cost optimization (FinOps), cluster tuning, autoscaling configurations, and handling skewed data profiles.

CI/CD & DevOps: Experience with Infrastructure as Code (Terraform), data build tool (dbt), testing frameworks (PyTest), and automated Git-based workflows. Experience Level: 10+ years of experience in Data Engineering/Architecture, with at least 3+ years specifically leading large-scale cloud data migrations. Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

Preferred Certifications Databricks Certified Data Engineer Associate / Professional Databricks Certified Solutions Architect AWS Certified Database Specialist or equivalent Cloud Certifications

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