Job Description
The Senior Data Quality Engineering Analyst role will be responsible to take up lead level activities - participating in requirement understanding, test planning, review of test execution result, The role should be able to independently undertake validation of critical business applications and drive impact across the Taco Bell business through identification and driving resolution of key failure points of system landscape. With this role, the opportunities are endless: The Senior Data Quality Engineering Analyst will get to work with top business and technology minds in the business, able to successfully contribute to enormous growth trajectory of Taco Bell and thus growing and leading their own career path in corporate. This role will enable the candidate to work on exciting new technologies that are being used at over 8000 Taco Bell restaurants. The role has ample opportunities to bring in innovations in software test automation to improve the validation process. The Senior Data Quality Engineering Analyst will report to Principal Solutions Architect, Data Platforms.
Responsibilities
About the Job:
The Senior Data Quality Engineering Analyst role will be responsible to take up lead level activities - participating in requirement understanding, test planning, review of test execution result, The role should be able to independently undertake validation of critical business applications and drive impact across the Taco Bell business through identification and driving resolution of key failure points of system landscape. With this role, the opportunities are endless: The Senior Data Quality Engineering Analyst will get to work with top business and technology minds in the business, able to successfully contribute to enormous growth trajectory of Taco Bell and thus growing and leading their own career path in corporate. This role will enable the candidate to work on exciting new technologies that are being used at over 8000 Taco Bell restaurants. The role has ample opportunities to bring in innovations in software test automation to improve the validation process. The Senior Data Quality Engineering Analyst will report to Principal Solutions Architect, Data Platforms.
The Day-to-Day:
• 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 and be able to review test results of junior team members and be able to guide 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, callout out and socialize project risks so that applicable stakeholders can take informed decision
• 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, and referential integrity and business rule enforcement, while also 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 be able to deliver applicable automated test solution to provide appropriate solution within a stipulated timeframe
• Track quality assurance metrics, like defect leakage, defect densities and open defect counts
Qualifications
Is this you?
• 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 in different AWS services JSON and XML files, Snowflake database etc.
• Have at least 3 years of test script development experience for automated validation of application under test.
• Highly preferred experience to validate data quality within Key domains like Restaurant Front of House, Back of House, Customer etc.
• Maintains strong Partnership with data engineers to embed quality checks directly into pipelines
• Knowledge on developing and maintain automated testing frameworks for data pipelines and integrate with CI/CD processes for continuous validation
• Knowledge on 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 through the organization
• Passion to learn new technology and processes curiosity to collaborate with subject matter experts
Work-Hard, Play-Hard:
Hybrid work schedule and year-round flex day Friday
Onsite childcare through Bright Horizons
Onsite dining center and game room (yes, there is a Taco Bell inside the building)
Onsite dry cleaning, laundry services, carwash,
Onsite gym with fitness classes and personal trainer sessions
Up to 4 weeks of vacation per year plus holidays and time off for volunteering
Tuition reimbursement and education benefits
Generous parental leave for all new parents and adoption assistance program
401(k) with a 6% matching contribution from Yum! Brands with immediate vesting
Comprehensive medical & dental including prescription drug benefits and 100% preventive care
Discounts, free food, swag and... honestly, too many good benefits to name
Salary Range: $120,200 to $141,5400 annually + bonus eligibility + benefits
The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.
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