[Hiring] Data Quality Analyst / Data Tester @Poland and Middle-Eastern Europe

Role Description

The project involves migration of legacy and TMS-related data into Google BigQuery as part of a broader data platform modernization initiative. The team is responsible for:

• Designing ingestion frameworks
• Implementing transformation pipelines
• Ensuring data quality
• Delivering production-grade datasets for analytical consumption

Qualifications

• Strong SQL skills, including complex queries, joins, aggregations, window functions, and data comparisons
• Hands-on experience validating data across different systems, databases, or reporting platforms
• Proven experience with data quality testing, reconciliation, and validation of migrated data
• Ability to analyze discrepancies between source and target datasets and identify their root causes
• Experience validating ETL/ELT pipelines, including completeness, accuracy, consistency, and transformation logic
• Good understanding of data models, relationships, schemas, and data dependencies
• Experience testing structured and semi-structured data
• Ability to translate business and reporting requirements into test scenarios and validation rules
• Experience defining and executing data quality checks, including:
• Record counts and completeness
• Null and duplicate checks
• Referential integrity
• Field-level reconciliation
• Aggregation and KPI validation
• Business rule validation
• Historical data consistency
• Ability to distinguish between source data issues, transformation defects, and reporting/visualization issues
• Experience documenting defects and working closely with Data Engineers to investigate and resolve data discrepancies
• Good analytical and problem-solving skills
• Experience working with Git-based development workflows and Agile delivery teams

Requirements

• Hands-on experience with Google BigQuery
• Experience testing data migrations or reporting platform migrations
• Experience validating dashboards, reports, KPIs, and analytical datasets
• Understanding of ETL/ELT concepts and modern cloud data architectures
• Experience with automated or semi-automated data validation using SQL and/or Python
• Basic Python skills for data analysis, comparison, or test automation
• Experience with data profiling and identifying anomalies in large datasets
• Understanding of data quality dimensions such as accuracy, completeness, consistency, uniqueness, validity, and timeliness
• Experience working with APIs and validating externally sourced data
• Understanding of data lineage and the ability to trace data from source through transformations to the reporting layer
• Experience with defect management and test documentation
• Ability to work directly with business stakeholders to clarify expected reporting results and business rules

Benefits

• Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery
• Work from the European Union region and a work permit are required

Nice to Have

• Hands-on experience with Looker or another BI/reporting platform
• Experience with GCP Dataform tests or similar data testing frameworks (e.g. dbt tests)
• Experience in Retail or eCommerce
• Experience with reconciliation of sales, stock, product, customer, or transactional data
• Familiarity with Airflow / Cloud Composer
• Experience with data observability or data quality tools
• Understanding of CI/CD practices for data pipelines and automated data tests
• Experience with Google Cloud Platform and its data services
• Familiarity with Data Governance, metadata management, and data cataloguing
• Experience preparing or validating datasets used for Analytics, Data Science, or Machine Learning
• Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work
• Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches

Recruitment Process

• CV review
• HR call
• Interview
• Client Interview
• Decision