Senior Quality Assurance Engineer

Summary

Senior QA Engineer writes and maintains automated tests in Java to validate data ingestion and transformation for a US hedge fund's systematic trading platform.

Project description

US hedge fund develops and deploys systematic financial strategies across a variety of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on exploiting market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies - the foundation of a sustainable, global investment platform. Technologists at fund research, design, code, test and deploy projects while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually intense. Our teams are lean and agile, which means rapid prototyping of products with immediate user feedback. We seek people who think in code, aspire to solve undiscovered computer science challenges and are motivated by being around like-minded people. In fact, of the 600 employees globally, approximately 500 of them code on a daily basis. Fund success is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Great ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess a mindset of continuous improvement. That's a key ingredient in remaining a leader in any industry. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an exceptional talent. There is no roadmap to future success, so we need people who can help us create it. Our collective intelligence will drive us there.

Responsibilities

  • Your responsibilities will include: - Data Validation: Validate the accuracy, completeness, and consistency of output through data pipeline, ensuring it meets business requirements and quality standards. - Automation: Develop and maintain automation test cases using Python and/or Java to streamline data validation processes. - Collaboration: Work closely with data engineers, supporters, and other team to identify and resolve data-related issues. - Communication: Participate in discussions, provide updates, and collaborate with team members in English during daily work. Our ideal candidate will have a strong background in software testing, great quality awareness, and interpersonal skills. In addition, the candidate will have:
  • A bachelor's degree in a technical or quantitative field
  • At most 3-5 years of experience in data validation, data quality assurance, or similar roles.
  • Experience in Java/Python programming
  • Working experience on Linux
  • Good sense of quality assurance
  • Strong analytical, problem-solving and communication skills
  • C++ is plus
  • Experience with integration of data from multiple data sources a big plus
  • Details orientated and good sense of responsibility of keep high work standard and deliver the work on time
  • Good team player, easy-going and can adjust the working style proactively based on supervisor's feedback

SKILLS

Must have

  • - Data Validation Expertise: Experience in validating data pipelines, ensuring data accuracy, consistency, and alignment with business requirements. - Programming Skills: Proficiency in reading, understanding, and writing scripts in Java and Python for data validation and automation tasks. - Analytical Skills: Strong analytical and problem-solving abilities with a focus on identifying and resolving data quality issues. - Tool Proficiency: Basic understanding of Maven, Git, and Linux/Unix environments. - English Communication Skills: Ability to communicate effectively in English during daily work within a global team environment.

Nice to have

- Experience with Jenkins, Airflow for automation and workflow management. - Exposure to C++ is a plus, but not required. - Experience with AI Agents, including the use, development, or integration of AI Agent-based tools/workflows, is a strong plus. - Experience with LLM/ML-based testing or test case generation is an advantage.