Data Analysts / QA

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  

Job Description

We’re looking for a QA Data Engineer to support the validation, reconciliation, and production readiness of data pipelines for a high-impact enterprise initiative. This hybrid role is ideal for someone who combines strong analytical capabilities with hands-on experience in data quality, testing, and validation frameworks.

You will play a key role in ensuring data accuracy and reliability across multiple domains, working closely with Data Engineering and Analytics teams to validate and promote high-quality data pipelines into production.

What will you be doing?

• Validate data accuracy across pipelines, ensuring consistency between legacy and new systems.
• Build and maintain reconciliation frameworks to compare outputs between legacy and modernized data pipelines.
• Execute acceptance testing for data pipelines prior to production deployment.
• Validate identity resolution accuracy, including match rates and false positive/negative analysis.
• Develop and maintain automated regression test suites to ensure ongoing data quality.
• Perform data profiling and analysis to detect anomalies and inconsistencies.
• Document data lineage across multiple domains (up to 18 domains).
• Collaborate with Data Engineering and Analytics teams to ensure production readiness of data assets.

Qualifications

What are we looking for?

• 3+ years of experience in Data Quality, QA, or Data Analysis roles.
• Expert-level proficiency in SQL for data validation and analysis.
• Hands-on experience with data quality frameworks (Great Expectations preferred).
• Strong experience with Python for data validation, automation, or analysis.
• Experience with data profiling, reconciliation, and validation processes.
• Experience building or maintaining test automation frameworks for data pipelines.
• Strong attention to detail with a focus on data accuracy and reliability.
• Ability to work in cross-functional environments and collaborate effectively with engineering and analytics teams.

Nice to have

• Experience working with large-scale or distributed data platforms.
• Familiarity with modern data architectures and pipeline validation processes.
• Experience supporting production deployments and release validation processes.

Additional Information

Our 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. 

🛫 Travel opportunities to attend industry conferences and meet clients. 

👩‍🏫 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.