Responsibilities
- Validate changes to datasets against acceptance criteria provided by Product Owners and Development SMEs.
- Design, implement, and maintain automated test cases for data-driven software products, with mentorship from senior team members.
- Log and track issues when software behavior deviates from expected outcomes.
- Review feature requirements and provide actionable feedback to improve quality and clarity.
- Write clean, maintainable, and efficient code for automated testing frameworks.
- Collaborate within a cross-functional team including development, QA, product.
- Investigate, debug, and triage complex issues independently, escalating when necessary.
- Follow team best practices and contribute to continuous improvement efforts.
- Demonstrate curiosity and a growth mindset by learning from mistakes and seeking out the "why" behind tasks.
- Communicate clearly and proactively with team members and stakeholders.
- Display a willingness to implement AI tools to accelerate development and test cycles
Requirements
- 5+ years of proven experience in ETL process QA and data validation.
- Strong knowledge of Python for scripting and automation.
- Excellent SQL skills for data querying and validation.
- Hands-on experience with AWS, or other cloud services.
- Practical knowledge of Databricks and PySpark for working with big data.
- Familiarity with version control systems, especially GitHub.
- Hands-on experience working with data lakes and understanding of data warehousing concepts.
- Experience with Agile methodologies and iterative development.
- Familiarity with Elasticsearch and its querying capabilities.
- Familiarity with Airflow
Nice to Have
- Familiarity with GitHub Copilot and Claude Code
Tech Stack
Python, SQL, PySpark, AWS, Databricks, Elasticsearch, Airflow, GitHub
