QA Engineer

As a QA Engineer at MBC, your primary responsibilities will include designing and maintaining manual test scripts for internal products, building demo strategies for testing, implementing automated tests, and optimizing deployment strategies for our microservices in the cloud. Additionally, you'll analyze numerical strategy results with precision and work closely with the trading unit to align engineering products with business goals.

To qualify for the QA Engineer position at MBC, candidates should have a minimum of 2 years of experience with programming languages such as Javascript, C#, Java, C++, or Python, and at least 1 year of SQL experience. Candidates must also possess hands-on skills with Unix command line tools and be proficient in data analysis using relational databases, Excel, Google Sheets, and other tools.

The working environment for a QA Engineer at MBC is hybrid, based in the beautiful location of Dorado, Puerto Rico. This setup combines the flexibility of remote work with the collaborative energy of a local office, allowing you to engage with your team while enjoying the stunning local culture.

Preferred skills for the QA Engineer role at MBC include proficiency in C#, hands-on experience analyzing large datasets, familiarity with equity trading and automated trading systems, as well as direct experience in trading or an interest in the financial markets. These skills will help enhance your contributions to our team.

MBC offers its QA Engineer employees an attractive benefits package including a 401K plan, fully-compensated health insurance, paid time off (PTO), a signing bonus, and life concierge services. This comprehensive support shows our commitment to the well-being and career growth of our team members.

When developing test scripts as a QA Engineer, I start by understanding the requirements and features of the software. I then define the testing scope, and create detailed test cases before automating them where possible. My approach focuses on thorough documentation and collaboration with developers to guarantee accuracy and relevance.

To ensure the stability of automated trading strategies, I conduct comprehensive testing that includes stress tests, regression tests, and performance evaluations. I also utilize CI/CD pipelines to prevent issues during deployment, focusing on continuous monitoring and validation to ensure robustness.

In a cloud environment, I prefer using tools like Selenium for automated testing due to its versatility across different platforms. Additionally, I leverage cloud-native tools such as Jenkins for CI/CD, and monitoring tools like Grafana to visualize performance metrics.

When faced with conflicting priorities while testing software, I prioritize based on the project deadlines and business impact. Communicating with stakeholders throughout the process helps align on expectations, and I adjust my approach based on urgent requirements while ensuring essential tests are not compromised.

In a previous role, I identified a critical bug during regression testing when a trading algorithm failed to execute orders under certain market conditions. I immediately documented the issue, informed the team, and collaborated on a fix. This proactive approach minimized potential financial losses and bolstered the system's credibility.

When analyzing numerical results from trading strategies, I consider metrics like Sharpe Ratio, maximum drawdown, win/loss ratio, and overall profitability. These metrics provide a clear picture of strategy performance and help identify areas for improvement or adjustments needed.

To stay updated on the latest trends in software testing and trading, I regularly read industry blogs, participate in webinars, and engage with professional communities online. Networking with fellow professionals allows me to share insights and keep my knowledge current in this fast-paced field.

I have extensive experience with SQL for data testing, which includes writing complex queries to validate data integrity, performing data migrations, and ensuring that data analytics outputs align with the expected values. SQL proficiency enables me to efficiently manage and test large datasets.

During a testing phase, I once collaborated closely with business stakeholders by setting up regular check-in meetings to discuss testing progress and gather feedback. This communication ensured alignment on expectations and allowed us to adapt our testing strategy based on business priorities.

I believe a QA Engineer needs to think like a trader because understanding the trading mindset helps ensure that testing aligns with business objectives. By approaching testing with an awareness of market dynamics and user behavior, I can identify critical areas for testing and deliver higher-quality products.