Senior QA Engineer
WHAT IS THE OPPORTUNITY?
Capital Markets Quantitative & Technology Services – Data AI and Research Technology (DART) team is hiring a hands-on Sr. Quality Automation Engineer to test cutting edge AI solutions for Investment Research, Banking, Sales and Trading.
Quantitative & Technology Services (QTS) delivers innovative solutions for RBC Capital Markets in a strong partnership with Technology & Operations (T&O). We are a cross-asset development organization focused on providing our clients with a modern and quantitative platform. We leverage Digital, Data and AI to deepen our client relationships. We support our clients in Lending & Finance, Advisory & Origination and Client Trading & Market Making. We have commercial products that are helping out customers navigate cash management (RBC Clear) and electronic trading (Aiden).
You’ll be part of a team working on GenAI Initiatives, testing systems that orchestrate models, tools and data into intelligent, context-aware pipelines.
WHAT WILL YOU DO?
- Implement and champion best practices in Quality engineering, supporting the implementation of the QE Program and overall QE process and standards through continuous test preparation and execution, leveraging an engineering mindset created by practicing deep, technical and domain expertise.
- Responsible for reviewing requirements and business functions
- Creating and maintaining end to end test automation frameworks on-prem and in cloud using Python.
- Responsible for designing the effective automated test frameworks and data-driven execution approach and test design techniques, suggesting and implementing improvements to the test automation processes and tooling.
- Train and mentor junior members of the team to help solidify their automation and testing expertise.
- Manual testing is to be expected, but emphasis will be placed on devising and implementing test automation.
- Develop standardized procedures – test strategies and plans, regression, integration, end to end testing, automated test cases.
- Working with Data Bricks, Snowflake and Azure, testing data hops through the different stages of transformation.
- Continuously identify potential issues, conflicts, and risks. Analyze, mitigate, and escalate where appropriate.
- Collaborate and contribute on cross-functional enterprise initiatives and manage the effective implementation of assigned deliverables.
Must have:
- Minimum 5+ years of experience in a QE/ Agile environment with a focus on technical, automated validations leveraging variety of tools/ technologies/ frameworks.
- Undergraduate degree in Technology
- Strong Python-coding skills, with focus on Spark/PySpark
- Strong QA or Development background with focus on delivering excellent, well-tested, quality software into production, taking on the role of gatekeeper to production.
- Must have implemented and be very familiar with CI/CD pipelines.
- Strong communicator with good organizational and time management capabilities, able to establish good working relationships across teams.
- Deadline-driven and results-oriented; able to meet consistently high-quality standards while handling a variety of tasks and deadlines simultaneously.
Nice-to-have:
- Post Graduate degree in Data Science.
- Experience working with Models
- Experience developing or testing AI Frameworks.
- Cloud-related experience.
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Job Skills
Application Testing, Automated Testing, Collaborating, Computer Science, Data Science, Decision Making, Detail-Oriented, End-to-End Testing, IT Quality Assurance, Long Term Planning, Manual Testing, Microsoft Azure, Predictive Analytics, Programming Languages, PySpark, Python (Programming Language), Quality Assurance (QA), Software Product Testing, Teamwork, Test Automation, Test Automation Framework, Test Case Design, Testing Strategies