MCPNew: Mokaru MCP server is live
Blend360

Blend360

Data QA Analyst

Company

Blend360

Role

Data QA Analyst

Job type

Full-time

Found on Mokaru

🔥Recently

Share this job

Salary

Not disclosed by employer

Job description

What is this position about?

We are looking for a Data QA Analyst with experience in Azure and Databricks to ensure data quality, reliability, and consistency across modern data platforms. This role focuses on validating data pipelines, implementing automated quality checks, and collaborating closely with Data Engineering and business teams to guarantee accurate and production-ready data assets.

  • Design and implement a data quality framework across Bronze, Silver, and Gold layers — defining validation rules, threshold tolerances, and alerting standards
  • Build and maintain automated data quality checks within Databricks pipelines — row counts, null checks, referential integrity, schema validation, and business rule assertions
  • Own reconciliation between source systems and Databricks layers — ensuring source data lands accurately and transformations produce expected outputs
  • Validate identity resolution outputs in the Silver layer — reviewing match rates, investigating false positives and false negatives, and ensuring enterprise identifiers are being assigned correctly across source populations
  • Perform end-to-end pipeline testing — validating that data flows correctly from ingestion through to the Gold layer and that downstream reporting outputs reflect accurate data
  • Partner with Data Engineers to define acceptance criteria for each sprint’s pipeline and data model deliverables before they are promoted to production
  • Support UAT with client business stakeholders — helping them validate that Gold layer outputs meet their reporting requirements
  • Document all QA processes, test results, and data quality findings in a format that can be handed off to the client team at engagement close
  • Monitor pipeline health post-deployment — investigating and triaging data quality incidents and working with engineers to resolve root causes quickly
  • Experience working with Azure-based data platforms, including Databricks.
  • Strong understanding of data quality frameworks and testing methodologies for data pipelines.
  • Experience validating ETL/ELT processes and working with layered architectures (Bronze, Silver, Gold).
  • Strong SQL skills and experience analyzing large datasets.
  • Experience implementing automated data validation and reconciliation processes.
  • Familiarity with data pipeline monitoring, alerting, and troubleshooting.
  • Ability to collaborate with Data Engineers and business stakeholders.
  • Strong analytical thinking and attention to detail.
  • Experience documenting QA processes and results in a structured manner.

What about languages?

  • English: Advanced (required for effective communication with global teams).

How much experience must I have?

  • 1+ years of experience in Data Quality, Data Engineering, or Data Analysis roles.

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!

Resume ExampleCover Letter Example

Explore more