QA Lead with Data Quality Experience

POSITION: QA Lead with Data Quality Experience

Work location: 100% remote

Start: ASAP

Cooperation form: B2B with ITFS

Rate: 140-160 PLN/h + VAT

Recruitment process: Short phone call with an ITFS recruiter -> Technical interview -> Project interview -> Decision

Daily tasks

• Creating and implementing test strategies for data platforms (ETL/ELT, Data Lake, DWH, AI/LLM).
• Planning, prioritizing, and supervising QA activities in an Agile/Scrum process.
• Comprehensive management of testing (functional, integration, UAT, performance, automated) and risk.
• Verifying data quality, consistency, and correctness (source-to-target, data reconciliation).
• Defining data test automation processes and their integration with CI/CD.
• Managing the QA team: task allocation, mentoring, and development of quality processes.
• Error analysis (Root Cause Analysis), incident supervision, and quality reporting (KPI, Test Completion Report).
• Managing environments and test data, as well as ensuring requirements traceability.
• Testing non-functional areas (performance, resilience, retry/idempotency mechanisms).
• Close cooperation with business, developers, and architects, and ensuring compliance with audits and regulations.

Requirements

Min. 10 years of experience in QA, including min. 5 years as a QA Lead / Leader.

Management of data testing and ETL/Data Testing programs in an Agile environment.

Very good knowledge of ETL/ELT in Data Warehouse, Data Lake, and Lakehouse architecture.

Advanced SQL and practice in data validation and profiling.

Experience in source-to-target validation, data reconciliation, and data quality testing.

Practical knowledge of: Azure Data Factory, Databricks, Delta Lake, and Spark/PySpark.

Knowledge of Python, PyTest, REST API testing, CI/CD pipelines, and automation frameworks.

Designing and implementing test automation strategies.

Knowledge of data observability, monitoring, and Data Quality tools.

Experience in testing financial data, reporting, and regulatory processes.

Basics of XBRL (Taxonomies, Facts, Contexts, Units, XML, Arelle) and knowledge of CDM and STRATA.

Experience in validating data from OCR and financial statements.

Testing AI/LLM solutions (prompt testing, benchmarks, hallucination detection, grounding, model drift).

Testing Agentic AI in terms of orchestration, task execution, and corrective processes.

Managing distributed teams and collaborating with interdisciplinary teams.

Higher education (Computer Science/Engineering) and advanced English.

Nice to have:

ISTQB Advanced Test Manager or Test Analyst certification,

Certified Scrum Master (CSM) or SAFe Agile Certification,

Microsoft Azure Data Engineer Associate certification,

Databricks Fundamentals Certification,

Certifications in the field of AI/ML Testing or Data Quality.

Must have: ETL, Python, QA, pytest, REST API, SQL