Data Quality & Governance Manager

Nacre Capital; España; Presencial; EUR 50.000 - 70.000; Jornada completa

Descripción de la vacante

A leading technology organization in Spain seeks a Data Quality & Governance Manager to ensure the integrity and consistency of its expanding data ecosystem. The role involves designing data quality frameworks, enforcing data standards, and collaborating with cross-functional teams. Required qualifications include experience in data quality management, strong analytical skills, and proficiency in SQL and data validation tools. This position is essential for maintaining trust in the platform.

Formación

• Proven experience in data quality management or governance.
• Strong analytical skills and attention to detail.
• Solid understanding of data modeling and database management.
• Experience with data validation and monitoring tools.

Responsabilidades

• Design, implement, and maintain data quality frameworks.
• Enforce standards for data accuracy and consistency.
• Collaborate with data engineers and analysts to ensure quality.
• Lead root cause analysis for data discrepancies.
• Establish and monitor KPIs related to data health.

Conocimientos

Data quality management

Analytical skills

Data modeling

ETL processes

SQL

Python

Communication skills

Herramientas

MSSQL

Data validation tools

Descripción del empleo

About EveryWatch

EveryWatch is a cutting-edge startup at the intersection of luxury and technology. Focused on the high-end watch market, we provide comprehensive data insights to collectors, retailers, enthusiasts, and major brands, serving both B2C and B2B audiences. By leveraging AI, advanced analytics, and proprietary digital tools, we bring clarity and transparency, helping our users make smarter decisions with confidence.

Role Overview

We're seeking a Data Quality & Governance Manager to ensure the integrity, accuracy, and consistency of EveryWatch's expanding data ecosystem. This role is central to maintaining trust in our platform by ensuring that data across all sources is reliable, complete, and aligned with business and analytical needs. You will define and oversee data quality standards, implement validation frameworks, monitor ongoing data health, and collaborate with engineering, analytics, and product teams to continuously improve data reliability.

This is an ideal role for someone passionate about clean, consistent, and meaningful data - a person who thrives on building scalable processes and ensuring that everyone in the company can make decisions with confidence.

Key Responsibilities

• Design, implement, and maintain data quality and governance frameworks across the organization.
• Define and enforce standards for data accuracy, completeness, and consistency across systems.
• Develop and automate data validation rules, checks, and alerts to identify and correct data anomalies.
• Collaborate with data engineers, analysts, and product managers to ensure data pipelines and models adhere to quality standards.
• Lead root cause analysis for data discrepancies and coordinate corrective actions.
• Maintain a comprehensive data dictionary, ownership documentation, and metadata catalog.
• Establish and monitor KPIs related to data health, reliability, and completeness.
• Promote a data quality culture across teams, training stakeholders in best practices and standards.
• Contribute to the continuous improvement of data architecture, workflows, and integration processes.

Requirements

• Proven experience in data quality management, data governance, or data stewardship.
• Strong analytical skills and meticulous attention to detail.
• Solid understanding of data modeling, ETL processes, and database management (MSSQL experience preferred).
• Experience with data validation and monitoring tools or scripting (SQL, Python, or similar).
• Excellent communication and collaboration skills - ability to work cross-functionally with technical and non-technical teams.
• Comfortable developing and enforcing data standards and documentation.
• Ability to prioritize and manage multiple data quality initiatives simultaneously.
• A proactive, process-driven mindset with a strong sense of ownership and accountability.
• Experience in a data-heavy, fast-paced environment such as a tech startup or analytics company is a plus.
• Excellent written and spoken English is a must.