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.
Job DescriptionWe are looking for a QA Analyst with strong technical skills to validate data pipelines, backend systems, and integrations. In this role, you will perform automation, data validation, performance, and end-to-end testing across modern data platforms. You will analyze requirements, design test scenarios, build test data workflows, and maintain regression suites to ensure data accuracy, reliability, and system compatibility.
Key Responsibilities
- Validate ETL/ELT pipelines, data transformations, schema, and mappings.
- Perform data quality checks (accuracy, completeness, consistency, timeliness).
- Test API integrations and validate data flow across systems.
- Support testing of batch, streaming, and event-driven pipelines.
- Create automation and data validation scripts using Python.
- Execute regression, smoke, and integration testing.
- Conduct performance and load testing using JMeter.
- Identify defects, negative scenarios, flaky tests, and root causes.
- Improve test coverage and automation frameworks.
Required
- Experience testing data pipelines, ETL/ELT processes, and backend systems.
- Strong Python skills for automation and data validation.
- Experience with API testing and automation tools (e.g., Playwright).
- Familiarity with performance testing tools such as JMeter.
- Strong understanding of data quality validation and debugging pipelines.
Nice to have
- Experience with AI prompt testing and output validation.
- Knowledge of security/compliance testing and PII protection.
- Experience with Cucumber/Gherkin, Arize Phoenix, or Postman.
- Experience with end-to-end data flow testing and detecting data drift or loss.
What about languages?
Advanced English proficiency is required for effective communication with international teams and stakeholders.
How much experience must I have?
We are looking for candidates with 3+ years of experience in QA, Data QA, or Data Engineering testing.
Additional InformationOur Perks and Benefits:
📚 Learning Opportunities:
- Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
- Access to AI learning paths to stay up to date with the latest technologies.
- Study plans, courses, and additional certifications tailored to your role.
- Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
- English lessons to support your professional communication.
👩🏫 Mentoring and Development:
Career development plans and mentorship programs to help shape your path.
🎁 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.
Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.
Skills Required
- Experience testing data pipelines, ETL/ELT processes, and backend systems.
- Strong Python skills for automation and data validation.
- Experience with API testing and automation tools (e.g., Playwright).
- Familiarity with performance testing tools such as JMeter.
- Strong understanding of data quality validation and debugging pipelines.
Blend360 Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Blend360 and has not been reviewed or approved by Blend360.
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Fair & Transparent Compensation — Pay is considered fair-to-good by many, and public salary postings for common data roles indicate competitive packages in numerous markets. Feedback suggests overall company sentiment aligns with acceptable compensation relative to peers in consulting and analytics.
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Flexible Benefits — Flexible and remote/hybrid work arrangements are consistently highlighted in official materials and role descriptions. Feedback suggests flexibility is a meaningful part of the total rewards experience.
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Retirement Support — A 401(k) with company match is part of the core package. Feedback suggests retirement offerings are standard and contribute to a complete benefits set.
Blend360 Insights
What We Do
Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. Blend360 has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace.
