QA professional to $6000

What you'll own:

The quality frontier of enterprise Data & Analytics.

Not testing UI features. Not validating APIs.

Testing entire data ecosystems—from raw ingestion to business-ready insights.

Your mission: (if you should accept it)

Lead quality engineering strategy across Microsoft Fabric, Azure Integration Services, Informatica IDMC, and TIBCO EBX.

You'll embed automated data validation, lineage checks, and regression testing directly into CI/CD pipelines—ensuring every pipeline is robust, reliable, and built for scale.

Day-to-day, you'll:

→ Integrate Agile and DevOps principles across data pipelines (ITIL v4, DataOps)

→ Embed data quality checks into Azure DevOps CI/CD workflows

→ Implement regression testing across multi-environment ADF and Informatica pipelines

→ Validate mission-critical dataflows with failover and resilience scenarios

→ Test Fabric 'Medallion Architecture' and Azure Data Lake Gen2 configurations

→ Write validation queries in T-SQL and Python for data platform testing

→ Apply AI/ML-driven quality assurance techniques

→ Pressure-test with simulated outages, queue backlogs, timeout conditions

You're the right fit if you have:

Must-haves:

✓ ISTQB Advanced Test Manager (or equivalent demonstrable experience)

✓ ITIL v3/v4 Foundation or equivalent IT Service Management qualification

✓ QA leadership in agile, product-focused IT (ideally financial services)

✓ Dev-level technical skills: T-SQL, Python, Azure Data Factory, Power Query (M), DAX, XMLA

✓ Microsoft Fabric testing experience (Medallion Architecture)

✓ Azure Databricks and Azure Data Lake Gen2 validation expertise

✓ CI/CD automation using Azure DevOps

✓ Data platform configuration and dataflow testing

Strong advantages:

✓ AI/ML approaches for quality efficiency and defect identification

✓ NIST Cybersecurity Framework (CSF) familiarity

✓ EU Digital Operational Resilience Act (DORA) knowledge

✓ Power BI / Analytics testing skills

✓ PySpark, Delta Lake, Fabric Notebooks experience

✓ REST/Graph API validation

What makes this unique:

Most QA roles test applications.

This role tests platforms.

You'll validate data engineering solutions, test BI semantic models, and ensure resilience across complex data ecosystems that support regulatory compliance and strategic decision-making.

Technical depth required:

This isn't manual testing. You need:

→ Ability to write T-SQL validation queries

→ Python scripting for data validation

→ Running Data Factory pipelines and dataflows

→ DAX/XMLA for tabular model testing

→ Understanding Fabric Notebooks, Delta Lake, PySpark

This is development-level technical work applied to quality engineering.

Contract details:

Location: Sofia, Bulgaria (not remote)