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Robert Half are assisting a market leading financial services organisation to recruit an Data QA Engineer on an initial 6 month contract basis
Role
- The Data QA Engineer will perform rigorous data validation and testing to support data migration efforts, ensuring high standards of data quality and integrity.
- Collaborate with data engineering on ELT testing, specifically in identifying and troubleshooting errors in data movement and transformation processes.
- Establish and implement automated data validation frameworks that ensure data accuracy, consistency and reliability across our data pipeline.
- Create and maintain CI/CD-integrated QA workflows to support real-time testing and automated quality checks, focusing on Azure and Snowflake infrastructure.
- Develop automated test cases for data validation, focusing on critical workflows, data transformations, and API integrations within both Snowflake and Azure. Collaboration & Support for Data Engineering
- Work closely with the Senior Data Engineer to set and maintain quality standards for the Snowflake data warehouse, supporting scalability and reporting needs.
- Participate in data architecture discussions, providing QA insights on best practices for data collection, transformation, and loading processes to maintain end-to-end quality.
- Ensure data reliability and accuracy by proactively identifying potential data discrepancies and issues, particularly API data integration, CI/CD workflows.
- Develop reusable, modularised test scripts in Python and SQL to streamline testing across various stages of the data pipeline.
- Conduct regular data cleansing activities, identifying, documenting, and addressing data anomalies within the financial lending dataset.
Profile
- The Data QA Engineer will have solid understanding of the data lifecycle, including experience with data collection, transformation, cleansing, validation, and testing in complex environments.
- Familiarity with data integration tools like FiveTran and proficiency in SQL for testing data accuracy and consistency. Technical Proficiency
- Hands-on experience with data validation in Snowflake or similar cloud data warehouses, including data testing and quality checks in SQL views.
- Proficiency in SQL and Python for advanced data validation and data quality assurance automation.
- Knowledge of Azure and Azure DevOps for managing QA within CI/CD pipelines, including experience with containerised environments.
- Familiarity with automated data validation and monitoring tools within Snowflake and Azure, focusing on real-time error detection and alerting.
- Knowledge of data automation tools and scripting for streamlined data QA processes. Financial Sector Familiarity (Preferred)
- Experience in financial lending or similar sectors, understanding industry-specific data requirements and quality assurance practices. Collaboration & Communication
Company
- Market leading financial services organisation
- Offices globally including London
Salary & Benefits
The salary range/rates of pay is dependent upon your experience, qualifications or training.
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