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Remote Reverse Engineering Jobs in Phoenix, AZ (NOW HIRING)

Koantek

Databricks Platform Architect

Chandler, AZ · Remote

Remote Position Type: Contract Job Overview We are seeking an accomplished, technology-driven Lead ... Ability to reverse-engineer and refactor legacy database logic into distributed paradigms.

Shutterfly

Principal Software Engineer

Tempe, AZ · On-site +1

$131.30K - $176K/yr

This is a fully remote position based in US. First day onboarding will be onsite at the nearest hub ... What You'll Do Here: • Collaborate with engineering leaders, product management, key stakeholders ...

Shutterfly

Principal Software Engineer

Tempe, AZ · On-site +1

$131.30K - $176K/yr

This is a fully remote position based in US. First day onboarding will be onsite at the nearest hub ... What You'll Do Here: • Collaborate with engineering leaders, product management, key stakeholders ...

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All JobsRemote Reverse Engineering JobsRemote Reverse Engineering Jobs in Phoenix, AZ

Remote Reverse Engineering information

See Phoenix, AZ salary details

$81.4K

$135.3K

$193.6K

How much do remote reverse engineering jobs pay per year?

As of May 29, 2026, the average yearly pay for remote reverse engineering in Phoenix, AZ is $135,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,400.00 and $176,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Reverse Engineering Specialist, and why are they important?

To thrive as a Remote Reverse Engineering Specialist, you need strong analytical skills in software deconstruction, a solid understanding of programming languages (such as C/C++ and Assembly), and typically a degree in computer science or related experience. Proficiency with tools like IDA Pro, Ghidra, OllyDbg, and experience with debuggers and disassemblers is essential, as are relevant certifications such as CEH or OSCP. Critical thinking, problem-solving, and clear written communication are vital soft skills for documenting findings and collaborating remotely. These skills ensure accurate code analysis, effective vulnerability discovery, and secure communication when working independently or with distributed teams.

What are some common challenges faced by remote reverse engineers, and how can they be addressed?

Remote reverse engineers often face challenges such as limited access to proprietary hardware, difficulties in real-time collaboration, and ensuring secure handling of sensitive data. To address these, it's important to leverage secure remote desktop solutions, maintain clear documentation, and establish regular communication with team members. Additionally, using virtual labs and emulation tools can help overcome hardware access limitations, while participating in team debriefs ensures alignment and knowledge sharing.

What is remote reverse engineering?

Remote reverse engineering is the process of analyzing software, hardware, or systems from a remote location to understand their design, functionality, or vulnerabilities. This often involves using specialized tools to decompile code, inspect binaries, or analyze protocols without having physical access to the device or system. Remote reverse engineers may work on tasks such as malware analysis, software compatibility, or security assessments. The work typically requires strong knowledge of programming, cybersecurity, and networking, as well as familiarity with legal and ethical considerations.

What is the difference between Remote Reverse Engineering vs Remote Malware Analyst?

AspectRemote Reverse EngineeringRemote Malware Analyst
Required CredentialsKnowledge of assembly, debugging, and disassembly tools; sometimes certifications like GREM or GREM+Knowledge of malware behavior, analysis tools, and sometimes certifications like GREM or GREM+
Work EnvironmentPrimarily technical, involving code analysis and debuggingFocuses on analyzing malicious code and threat detection
Industry UsageUsed in cybersecurity, software development, and security researchPrimarily in cybersecurity, incident response, and threat intelligence

Remote Reverse Engineering and Remote Malware Analyst roles share skills like understanding binary code and using analysis tools. However, reverse engineers focus on dissecting software and systems, while malware analysts specialize in identifying and mitigating malicious threats. Both roles are vital in cybersecurity and often overlap in skills and tools used.

What are the most commonly searched types of Reverse Engineering jobs in Phoenix, AZ? The most popular types of Reverse Engineering jobs in Phoenix, AZ are:
What are popular job titles related to Remote Reverse Engineering jobs in Phoenix, AZ? For Remote Reverse Engineering jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Remote Reverse Engineering jobs in Phoenix, AZ look for? The top searched job categories for Remote Reverse Engineering jobs in Phoenix, AZ are:
What cities near Phoenix, AZ are hiring for Remote Reverse Engineering jobs? Cities near Phoenix, AZ with the most Remote Reverse Engineering job openings:
Remote Reverse Engineering jobs near you
Databricks Platform Architect

Databricks Platform Architect

Koantek

Chandler, AZ • Remote

Contractor

Posted 14 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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