Job Summary
Test Data Architect role for an international organization focused on designing and governing scalable test data solutions using Snowflake and DBT across hybrid work environments. The position involves defining reusable data patterns optimizing test data provisioning and ensuring high quality data practices that support efficient delivery for complex applications and asset management operations domains.
Responsibilities
- Design robust test data architecture leveraging Snowflake and DBT to enable reliable repeatable and efficient test data provisioning across multiple application platforms and environments ensuring alignment with enterprise data standards and quality objectives.
- DBT Snowflake Testing
- Develop and maintain advanced Snowflake tasks that orchestrate test data pipelines automate refresh cycles and synchronize datasets across non production environments optimizing performance and resource usage for large scale testing needs.
- Configure and refine DBT core projects to implement modular reusable models that transform raw data into structured well governed test datasets supporting complex analytical and transactional test scenarios with high consistency.
- Create and optimize DBT macros that encapsulate common transformation logic and validation rules for test data improving maintainability reducing duplication and enabling rapid adaptation of data flows to evolving testing requirements.
- Utilize DBT cloud capabilities to manage deployments run schedules and monitor test data transformations ensuring predictable pipeline behavior and clear observability for quality assurance and engineering teams.
- Collaborate with quality engineering and application development teams to analyze test data requirements define coverage criteria and design domain specific datasets that meet functional integration and performance testing objectives.
- Establish and enforce test data governance practices including data masking synthetic data generation and controlled data subsets to safeguard sensitive information while preserving data realism and usability for testing.
- Analyze and optimize Snowflake data models storage strategies and query patterns used for test data reducing execution time improving cost efficiency and ensuring scalability for growing volumes and complexity.
- Document end to end test data architecture including data lineage transformation logic and environment specific configurations enabling transparent onboarding easier troubleshooting and clear communication across stakeholders.
- Partner with operations and business analysts in asset management operations to understand key data flows position records and transaction lifecycles translating them into representative test datasets that support credible scenario based validation.
- Implement data quality checks and reconciliation routines within DBT models and Snowflake processes to detect anomalies ensure completeness and maintain high confidence in the reliability of test data used in critical validation cycles.
- Coordinate with environment management and release teams to integrate test data provisioning into continuous integration and continuous delivery processes reducing manual effort and enabling more frequent reliable releases.
- Mentor peers in effective use of Snowflake and DBT for test data sharing best practices and standards that enhance adoption of the architecture and contribute to more consistent data driven testing across the organization.
Qualifications
- Demonstrate deep hands on experience with Snowflake including tasks data modeling performance tuning and orchestrated processing specifically focused on enabling test data solutions for complex enterprise systems.
- Show advanced proficiency with DBT core and DBT cloud including design of modular projects development of reusable macros and configuration of automated runs that support high quality test data transformation workflows.
- Apply strong understanding of data warehousing and data engineering concepts such as dimensional modeling incremental loads and data quality frameworks to design resilient test data pipelines that support diverse test scenarios.
- Utilize analytical and problem solving skills to interpret testing requirements design appropriate data subsets and resolve issues in data flows ensuring that test data remains accurate timely and fit for each validation purpose.
- Bring domain exposure to asset management operations as a beneficial capability by translating business processes positions trades and reconciliations into realistic test datasets that improve relevance of system validation.
- Operate effectively in a hybrid work model by communicating clearly documenting decisions comprehensively and collaborating across time zones and locations while maintaining accountability for deliverables in a day shift.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
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