Blend is a premier AI services provider committed to co‑creating meaningful impact for its clients through data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by aligning human expertise with artificial intelligence to unlock value and foster innovation. Job Description 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. Experience 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. Languages English: Advanced (required for effective communication with global teams). Benefits Learning Opportunities: Certifications in AWS, Databricks, and Snowflake; access to AI learning paths, study plans, and additional certifications tailored to your role; access to Udemy Business; English lessons. Travel opportunities to attend industry conferences and meet clients. Mentoring and Development: Career development plans and mentorship programs. Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones; company‑provided equipment. Flexible working options to help you strike the right balance. Statutory Benefits: Social security coverage (IMSS); Christmas bonus (Aguinaldo) as per Mexican law; vacation premium (Prima Vacacional); remote work bonus; paid leaves as per Federal Labor Law (LFT); additional benefits as required by Mexican labor regulations. #J-18808-Ljbffr