Data QA Analyst at Blend360

Bogotá, Bogota D.C., Colombia -

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, Data Quality Frameworks, Great Expectations, Python, Data Profiling Techniques, Test Automation Strategies, Data Validation, Acceptance Testing, Data Lineage, Regression Testing, Anomaly Detection, Documentation, Communication, Match Rates, False Positives, False Negatives

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: 🏥 Health and Well-being: At-home medical assistance via EMI (or similar provider) through Asobursatil, available for all employees from AllStar to Analyst level. Private healthcare plans for Lead-level roles and above. 🎉 Celebrations and Recognitions: Christmas kit delivered to all employees. 1 day off for academic graduation. Family Day: 1 day off every semester (must be taken within the same semester). 💰 Financial Health and Savings (Work Together, Get Together Program): Savings incentive program via Asobursatil: Year 1: Blend contributes 50% of your monthly savings. Year 2: Blend contributes 100% of your monthly savings. Year 3+: Blend contributes 150% of your monthly savings. Savings can be withdrawn in July and December. 📚 Educational Loans and Subsidies: Forgivable education loans subject to committee approval and budget availability. Requirements: 1+ year at Blend, no disciplinary actions in the past 6 months, successful completion of prior training, and knowledge sharing within 6 months post-training. Retention-based forgiveness schedule applies after program completion. 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

The Data QA Analyst will validate data accuracy and ensure production readiness by collaborating with the Data Engineering Manager and Analytics Engineering Lead. They will design a reconciliation framework, execute acceptance testing, validate identity resolution accuracy, and document data lineage across multiple domains.