Senior Data Quality Engineering Analyst

Responsibilities

• Able to understand complex business process, technology landscape, related requirements and attend daily stand‑up meetings to focus on key focus areas of validation.
• Able to independently drive validation needs by creating comprehensive and well‑structured test plan, test scenario, test case, setting up test environment, working with business analyst and developer to understand requirements and architecture, reviewing test results of junior team members and guiding them with validation approach.
• Able to coordinate with key onsite and offshore counterparts to complete validation and certification activities within agreed upon project timeline.
• Able to identify, call out and socialize project risks so stakeholders can take informed decisions.
• Designing and implementing a comprehensive data quality framework involving building of automated validation framework across both batch and real‑time pipelines, enforcing core quality dimensions – completeness, accuracy, consistency, and timeliness – through checks like schema validation, data drift and anomaly detection, referential integrity and business rule enforcement, while defining and tracking KPIs and SLAs to continuously monitor and uphold data health across the organization.
• Embedding data quality controls within the pipelines involves integrating validation across the full data lifecycle, from ingestion through transformation to consumption, supporting both batch and streaming workloads.
• Able to bring in hands‑on development experience in test scripts to automate test process. Should deliver applicable automated test solution to provide appropriate solution within a stipulated timeframe.
• Track quality assurance metrics such as defect leakage, defect densities and open defect counts.

• Have a Bachelor of Science in Information Technology degree.
• Have at least 7 years’ thorough hands‑on experience in Quality Assurance Process.
• Have at least 5 years of experience with AWS services, JSON and XML files, Snowflake database, etc.
• Have at least 3 years of test script development experience for automated validation of applications under test.
• Highly preferred experience validating data quality within key domains such as Restaurant Front of House, Back of House, Customer, etc.
• Maintain strong partnership with data engineers to embed quality checks directly into pipelines.
• Knowledge of developing and maintaining automated testing frameworks for data pipelines and integrating with CI/CD processes for continuous validation.
• Knowledge of enabling reusable validation patterns using tools like dbt, Great Expectations, or custom frameworks.
• Passion to train and groom junior resources in the team and expand technical knowledge throughout the organization.
• Passion to learn new technology and processes, curiosity to collaborate with subject matter experts.

Demonstrates expertise in Quality Assurance processes, including the development of automated testing frameworks and data quality validation across various domains. Proficient in collaborating with cross‑functional teams to ensure data integrity and quality throughout the data lifecycle.

• AWS
• Snowflake
• Dbt
• Great Expectations
• CI/CD Processes