Data Governance Specialist - Barcelona

Your mission

• Establish and maintain a single source of truth for Customer Care data across all platforms and geographies.
• Define, document, and enforce data standards, taxonomies, and definitions so every team speaks the same data language.
• Partner with Data Analysts, Analytics Engineers, and Data Engineers to ensure data governance rules are embedded into tools and processes, not bolted on afterwards.

What you will do

• Build a global data hierarchy: create a top-down view of how granular data points roll up into strategic categories (e.g. grouping activity codes from tools like Calabrio or Zendesk into Productive Time, Shrinkage, and Lost Time) ensuring consistency across all sites and BPOs.
• Design and implement a tagging and classification process for agents, enabling reliable metadata capture across manual and automated workflows.
• Define and enforce consistent definitions across all data sources — ensuring that concepts like “Productive Hours” or “Handle Time” carry the same meaning in every tool and every location.
• Establish and maintain data refresh cadences, communicating proactively with owners of key data sources (e.g. Training, Workforce Management).
• Coordinate with Customer Care tooling owners to support the implementation of governance rules directly in source systems.
• Establish the Golden Record (Master Data Management): identify the authoritative source for each key data domain and resolve conflicts between systems.
• Own and maintain a comprehensive Data Dictionary documenting all available fields, their definitions, owners, and lineage, so any user knows exactly what they are looking at.
• Maintain a register of assumptions and changes — what changed, when, and why — enabling clear explanations of shifts in forecasts or metrics over time.
• Define the end-to-end data architecture for Customer Care, both conceptual (for business alignment) and logical (for database implementation), ensuring clear system boundaries and consistent integration across operational and analytical platforms.
• Establish and oversee data change management processes covering the full lifecycle (creation, modification, deprecation), ensuring changes are assessed for impact, properly documented, and communicated to stakeholders.
• Leverage AI-assisted tools to accelerate data classification, anomaly detection, and documentation. Identifying opportunities to automate repetitive governance tasks and free up capacity for strategic, high-value work.
• Drive a data literacy and self-service culture: run workshops and produce plain-language documentation to help non-technical stakeholders understand and trust the data they use.
• Monitor data quality KPIs (completeness, accuracy, timeliness, consistency) and own remediation when thresholds are breached.
• Act as the primary point of contact for data-related escalations from Customer Care operations, analytics, and leadership.

What you need

• University degree in Business Administration, Information Management, Computer Science, or a related field.
• 3+ years of experience in a data governance, data management, business intelligence, or analytics role.
• Proven ability to design and implement data taxonomies, classification frameworks, or data dictionaries in a complex, multi-system environment.
• Solid understanding of Master Data Management (MDM) principles and data lifecycle management.
• Proficiency in SQL for querying, validating, and auditing data across databases.
• Strong documentation skills and a structured, detail-oriented approach to problem-solving.
• Genuine curiosity for leveraging AI and automation to enhance governance workflows.
• Excellent communication skills in English.
• Comfortable working independently in a fast-paced, international environment with a high degree of ownership.

Bonus points for…

• Experience working with CRM, WFM, or contact-centre platforms (e.g. Salesforce, Zendesk, Calabrio, NICE) is a strong advantage.
• Experience with data cataloguing tools (e.g. Alation, OpenMetadata, Atlan, or dbt docs).
• Exposure to cloud data warehouses such as Snowflake, BigQuery, or Redshift.
• Understanding of data privacy regulations and their operational implications (GDPR, CCPA).
• Experience in a BPO, outsourcing, or multi-site Customer Care environment.