Data Quality Analyst / Data Tester (Bulgaria/Romania)

Responsibilities

Strong SQL skills, including complex queries, joins, aggregations, window functions, and data comparisons
Proven experience with data quality testing, reconciliation, and validation of migrated data
Ability to analyse discrepancies between source and target datasets and identify their root causes
Experience validating ETL/ELT pipelines, including completeness, accuracy, consistency, and transformation logic
Ability to translate business and reporting requirements into test scenarios and validation rules
Experience defining and executing data quality checks, including:
o record counts and completeness
o null and duplicate checks
o referential integrity
o field-level reconciliation
o aggregation and KPI validation
o business rule validation
o historical data consistency
Ability to distinguish between source data issues, transformation defects, and reporting/visualisation issues

Hands-on experience with Looker or another BI/reporting platform
Experience with GCP Dataform tests or similar data testing frameworks (eg. dbt tests)
Experience in Retail or eCommerce
Experience with reconciliation of sales, stock, product, customer, or transactional data
Familiarity with Airflow / Cloud Composer

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.

Hands-on experience validating data across different systems, databases, or reporting platforms
Good understanding of data models, relationships, schemas, and data dependencies

Experience documenting defects and working closely with Data Engineers to investigate and resolve data discrepancies

Experience working with Git-based development workflows and Agile delivery teams

Hands-on experience with Google BigQuery

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

Ability to work directly with business stakeholders to clarify expected reporting results and business rules
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.

review –

call –

Client

Decision