Data Quality Analyst

We are a team that develops and maintains analytical solutions and data management standards for an organization operating in a multi-system, multi-domain, and multi–data source environment.
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We are building a mature approach to data quality as an integral part of Data Governance so that data is reliable, comparable, and truly supports business decisions.
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We are looking for a Data Quality Analyst who will help us systematically improve data quality across the organization. Your main task will be to analyze datasets, define quality rules, and collaborate with business and technical teams on their implementation and monitoring. You will be the link between data, processes, and real business needs.

• Analyze datasets in terms of data quality (completeness, consistency, correctness, timeliness, etc.).
• Identify data quality issues and assess their impact on reporting, analytics, and business processes.
• Define Data Quality rules (business rules, technical rules, acceptance thresholds).
• Work with Data Owners and Data Stewards to refine data definitions and quality expectations.
• Translate business requirements into specific data quality rules and controls.
• Collaborate with technical teams on implementing DQ rules in tools and data pipelines and on data quality monitoring.
• Analyze data quality control results and recommend corrective actions.
• Participate in designing data quality management processes within the Data Governance framework.
• Co-create standards, documentation, and best practices in the Data Quality area.
• Support business teams in understanding data quality issues and their consequences.

• Experience in data analysis within data warehouse, data lake, or source system environments.
• Ability to analyze data using SQL, Python, SparkSQL, or similar technologies.
• Ability to work with both business and technical teams.
• Practical understanding of Data Quality topics and working with data in an organization, based on hands-on experience rather than just definitions.
• Understanding of concepts such as Data Owner, Data Steward, data definition, and system of record/single source of truth.
• Analytical mindset, ability to ask the right questions and get to the root causes of problems.
• Knowledge of English (reading documentation, project collaboration).

• Experience with Data Quality tools (e.g. Great Expectations, Ataccama, Talend DQ, Collibra DQ or similar). ​
• Experience in Data Governance or metadata management projects. ​
• Experience working in environments with many source systems and complex data flows. ​
• Ability to document quality rules and decisions (data catalog, Confluence, knowledge repositories). ​
• Knowledge of basic data lineage and data quality monitoring concepts.