Data QA Analyst at Blend360

Montevideo, Montevideo, Uruguay -

Full Time

Start Date

Immediate

Expiry Date

17 Aug, 26

Salary

0.0

Posted On

19 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, Data Validation, Data Profiling, Great Expectations, Test Automation, Data Lineage, Acceptance Testing, Regression Testing, Identity Resolution

Industry

Professional Services

Description

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com We are seeking a Data QA Analyst to contribute to our next level of growth and expansion. Job Description What is this position about? Validate data accuracy and ensure production readiness by working closely with the Data Engineering Manager and Analytics Engineering Lead across 18 data domains. Design and build a reconciliation framework to systematically compare legacy pipeline outputs against new pipeline outputs, identifying discrepancies and gaps. Execute structured acceptance testing for each pipeline prior to promotion to production environments. Validate identity resolution accuracy through rigorous analysis of match rates, false positives, and false negatives. Document end-to-end data lineage across all 18 domains to support auditability, transparency, and regulatory compliance. Build and maintain automated regression test suites to enable continuous quality assurance as pipelines evolve. Qualifications Expert-level SQL skills, with demonstrated ability to write complex queries for data validation, profiling, and reconciliation at scale. Experience with data quality frameworks, with preference given to candidates with hands-on Great Expectations expertise. Proficiency in Python for scripting automated tests, data profiling tasks, and quality checks. Strong background in data profiling techniques, including distribution analysis, completeness checks, and anomaly detection. Experience designing and executing test automation strategies in data or analytics engineering contexts. Ability to clearly document findings and communicate data quality issues to both technical and non-technical stakeholders. What about languages? English: Advanced (required for effective communication with global teams). How much experience must I have? 3+ years of experience in Data Quality, QA, or Data Analysis roles, with proven ability to build reconciliation frameworks and execute end-to-end acceptance testing across complex data pipelines. Additional Information Our Perks and Benefits: 🍽️ Every day lunches! (headquarters): Vegetarian, vegan, gluten and sugar free options. Gourmet meals every Friday with our on-site chef! ⚖️ Flexible working options to help you strike the right balance. 💻 All the equipment you need to harness your talent (Macbook and accessories). 🍎 Snacks and beverages available everyday (headquarters). 🎉 After office events, football, tennis and game nights (headquarters). ⚽ Everyone is welcome to join our football league every Wednesday's and Friday's. 🎱 Challenge your teammates to a pool game and win the office's trophy! 🎾 Tennis courts available for friendly matches. 🎮 Not a sports person? Don't worry, we also have chess championships, game and music nights for you to join! 📚 Learning opportunities: AWS Certifications (we are AWS Partners). Study plans, courses and other certifications. English Lessons. Learn from your teammates on our Tech Tuesdays! 🧭 Mentoring and Development opportunities to shape your career path. 🎁 Anniversary and birthday gifts. 📍 Great location and even greater teammates! So what are the next steps? Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we'll explore working together!

Responsibilities

Validate data accuracy and production readiness across 18 data domains by building reconciliation frameworks and executing acceptance testing. Document end-to-end data lineage and maintain automated regression test suites to ensure continuous quality assurance.