Performance Engineer.

Performance Engineer

I am seeking a Performance Engineer to join a great white label iGaming platform provider. The role is fully remote from Asia.

As a Performance Engineer, you will be instrumental in ensuring the scalability, reliability, and performance of our systems to deliver exceptional user experiences. Your mastery of performance testing tools, deep understanding of system architecture, and expertise in code and database optimization will drive the creation of high-performing, resilient applications. Reporting to the Head of Technology and collaborating closely with SRE, development, and database teams, you will lead performance testing initiatives, conduct bottleneck analysis, and implement optimization strategies. Your success will be defined by your ability to deliver robust performance solutions, maintain exceptional system reliability, and foster a culture of technical excellence, collaboration, and continuous improvement.

Key Responsibilities

1. Performance Testing & Analysis
- Lead all aspects of performance testing, including requirements gathering, test planning, script development, test data creation, execution, and comprehensive reporting.
- Design, execute, and analyze performance tests using a suite of tools, including but not limited to Microfocus LoadRunner, JMeter, Gatling, and k6, ensuring accurate simulation of production workloads.
- Conduct bottleneck analysis using advanced monitoring tools and Application Performance Management (APM) platforms (e.g., Dynatrace), identifying performance issues at the system, application, or database level.
- Develop workload models based on production statistics, designing realistic load patterns to simulate peak traffic and edge cases.
- Collaborate with SRE teams to collect and analyze production environment statistics, ensuring load profiles are accurate and reliable.

2. System Architecture & Optimisation
- Leverage a deep understanding of system architecture, including caching, distributed systems, Kubernetes (k8s) architecture, and networking, to identify and resolve performance bottlenecks.
- Perform code profiling and optimisation, applying expertise in algorithm selection, data structure efficiency, memory management, and concurrency patterns to enhance application performance.
- Optimise system configurations and infrastructure to support scalability and low-latency performance under high load.

3. Database Performance Optimisation

- Conduct SQL database performance testing, profiling, and tuning, optimizing query performance, indexing strategies, and caching mechanisms to ensure efficient data access.
- Apply deep knowledge of database systems (e.g., relational, NoSQL) to implement performance improvements, minimizing latency and resource utilisation.
- Collaborate with database administrators to refine database parameters and configurations for optimal performance.

4. Monitoring & Observability
- Implement advanced monitoring and observability practices, utilizing tools like Dynatrace to generate real-time performance metrics and actionable insights.
- Develop and maintain dashboards to track key performance indicators (KPIs), enabling proactive identification of performance degradation.
- Ensure comprehensive logging and tracing mechanisms are in place to support root cause analysis and performance troubleshooting.

5. Collaboration & Stakeholder Communication
- Engage actively in sprint planning, performance reviews, and cross-functional team meetings, contributing insights on performance feasibility and optimization strategies.
- Clearly articulate performance bottlenecks, trade-offs, and optimization rationales to developers, SREs, and stakeholders, documenting decisions for transparency.
- Work closely with development teams to align on performance goals, ensuring code and system changes meet performance standards.
- Bridge technical and operational discussions, fostering alignment between performance objectives and business requirements.

6. Leadership & Mentorship
- Mentor junior engineers on performance testing, profiling, and optimization techniques through pair programming, code reviews, and knowledge-sharing sessions.
- Lead workshops or tech talks on topics such as performance testing tools, observability practices, or database optimization, driving team-wide proficiency.
- Propose tools or processes (e.g., new testing frameworks, profiling tools) to enhance performance engineering efficiency, justifying recommendations with evidence.
- Model a data-driven, solution-oriented approach, inspiring team members to prioritize performance and reliability.

7. Professional Conduct & Team Culture
- Maintain a collaborative, respectful demeanor in all interactions, upholding the company´s values of integrity, innovation, and collaboration.
- Promote a culture of precision and technical excellence by sharing performance insights and encouraging open feedback within the team.
- Address performance challenges professionally, escalating issues with clear context and proposed solutions.

Key Performance Indicators (KPIs)

1. Performance Testing Accuracy & Quality (30%)
- Achieve 95% accuracy in workload models and load patterns, validated by production performance alignment and SRE reviews.
- Maintain an average test report approval rating of 90% or higher, with feedback emphasizing clarity and actionable insights.
- Implement at least one performance testing process improvement (e.g., automated test scripting) per quarter, reducing testing time by 10% or more.

2. System & Code Performance (25%)
- Ensure system performance metrics (e.g., response times, throughput) meet or exceed targets in 95% of releases, as measured by APM tools.
- Reduce performance-related bugs to fewer than 3 critical issues per release cycle, tracked via Jira.
- Deliver at least one code or system optimization per review cycle, improving latency or resource utilization by 10% or more, validated by profiling metrics.

3. Database Performance Optimisation (20%)
- Optimize at least 90% of identified slow queries or database bottlenecks within sprint timelines, improving query execution time by 15% or more.
- Implement indexing or caching improvements adopted in at least two production systems per review cycle, as validated by database administrators.
- Maintain database performance metrics within target thresholds for 95% of releases, as measured by monitoring tools.

4. Collaboration & Communication (15%)
-Attend 100% of performance reviews and team meetings unless approved otherwise, with active contributions noted by the Head of Technology.
- Produce clear documentation for 80% of major performance optimization decisions, accessible to developers and SREs.
- Receive positive collaboration feedback from at least two cross-functional team members (e.g., developers, SREs) per review cycle.

5. Leadership & Team Development (10%)
- Mentor at least one junior engineer per quarter, improving their performance testing or optimization skills, as documented by the Head of Technology.
- Lead one knowledge-sharing session per review cycle on performance engineering topics, with positive attendance and feedback.
- Propose and implement one team-wide performance process improvement annually (e.g., automated monitoring dashboards), adopted by the team.

Requirements

- Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent professional experience demonstrating advanced performance engineering skills.
- Minimum of 5 years of performance engineering experience, with at least 3 years specializing in performance testing and system optimization, evidenced by a portfolio showcasing measurable performance improvements.
- Mastery of performance testing tools, including but not limited to Microfocus LoadRunner, JMeter, Gatling, and k6, with demonstrated ability to design and execute complex load scenarios.
- Deep understanding of system architecture and networking, including caching, distributed systems, Kubernetes (k8s) architecture, and networking protocols, with experience optimizing distributed environments.
- Advanced monitoring and observability skills, with proficiency in tools like Dynatrace for generating performance metrics and actionable insights.
- Expertise in code profiling and optimization, including algorithm selection, data structure efficiency, memory management, and concurrency patterns, with a track record of optimizing application performance.
- Deep knowledge of database performance optimization, including query optimization, indexing strategies, and caching mechanisms, with experience improving database performance in production systems.
- Strong problem-solving skills, with the ability to balance performance, scalability, and technical constraints under tight deadlines.
- Excellent communication skills, with experience collaborating with cross-functional teams and presenting performance rationales to diverse audiences.
- Preferred: Experience with scripting languages (e.g., Python, Bash, JavaScript) for test automation, familiarity with cloud environments, or contributions to performance engineering frameworks.