Data Ops Analyst: Quality & Process Improvement (Madrid)

NielsenIQ; Madrid; On-site; EUR 22,000 - 25,000; Full time

Benefits offered by this job

Flexible working environment

Volunteer time off

Job summary

NielsenIQ in Madrid is seeking a Stat Ops Data Operations Analyst to ensure data accuracy across Consumer Panel Services. You will execute sample data operations, resolve data quality issues, and support country-specific projects while collaborating with Data Operations, Client Operations, and Data Science teams.

The role emphasizes monitoring data quality, driving process improvements, documenting findings, and contributing to harmonization across markets.

Qualifications

• Bachelor's degree in a technical field or final year candidates considered.
• Experience handling, manipulating and analyzing data.
• Working knowledge of SQL and database structures.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to work cross-functionally and manage priorities.
• Fluent English and fluent Spanish or Portuguese; based in Madrid.

Responsibilities

• Execute Stat Ops processes and support project work for the assigned market.
• Develop expertise in internal sample data tools and platforms.
• Collaborate with local Operations teams to ensure timely execution.
• Monitor data quality indicators and identify anomalies.
• Perform data quality reviews to ensure accuracy and consistency.
• Investigate data-related queries from internal teams.
• Support operational initiatives and continuous improvement projects.
• Contribute to harmonization and best-practices adoption.
• Document findings and recommendations for knowledge sharing.

Skills

Data analysis

SQL

Data quality

Documentation

English

Spanish/Portuguese

Education

Bachelor's degree in Statistics, Mathematics, CS or related

Master's degree preferred

Tools

SQL databases

Job description

NielsenIQ in Madrid is seeking a Stat Ops Data Operations Analyst to ensure data accuracy across Consumer Panel Services. You will execute sample data operations, resolve data quality issues, and support country-specific projects while collaborating with Data Operations, Client Operations, and Data Science teams.

The role emphasizes monitoring data quality, driving process improvements, documenting findings, and contributing to harmonization across markets.