Group IT Data Director

Konecta is a leading innovative global service provider in customer management business process and digital outsourcing, with 120,000 passionate employees working in 30 languages across 4 continents and 26 countries. Focusing on the unique needs and opportunities of each industry, Konecta offers a full range of end‑to‑end customer management solutions – including acquisition, retention, customer service, technical support, and collection – all based on a sustainable business model. These services are built on a portfolio of world‑class expertise covering customer experience and process management, digital solutions and cutting‑edge technologies. Headquartered in Madrid, Konecta delivers global revenues of €2 billion with more than 500 clients, covering some of the biggest names in telecoms, energy, banking, mobility, retail, and e‑commerce. Mission of the Role Group IT Data Director reports to the IT Group Program and Build Director and holds a strategic, central leadership role within the organization. He/She is responsible for defining the vision, architecture, and technical governance of all data assets across the Group. This role is pivotal in transforming raw data into a strategic asset, enabling advanced analytics, data‑driven decision‑making, and business innovation throughout all entities. The Group IT Data Director oversees the entire data platform—including data warehouses, data lakes, integration pipelines, and BI/Analytics tools—ensuring their reliability, quality, security, and compliance with relevant data protection regulations (e.g., GDPR, CCPA). This position plays a key role in establishing enterprise‑wide data standards, promoting data governance best practices, and supporting the development of a scalable and modern data ecosystem. Responsibilities Data Strategy and Architecture Define and evolve the Group’s Data Strategy in collaboration with the Chief Data Officer (CDO), if one exists, or directly with Executive Management and Business Lines. Design and maintain the target data architecture (modeling, flows, storage) to support the Group’s analytical and operational needs. Lead the selection, implementation, and management of Data Technology Platforms (Cloud Data Warehousing, Data Lake, ETL/ELT tools, MLOps solutions). Ensure the consistency of data models across all Group entities and systems. Technical Data Governance and Quality Establish and enforce technical data quality standards (profiling, cleansing, monitoring) to ensure the reliability of information. Implement the tools and processes for technical data governance (data dictionary, data lineage, metadata management). Collaborate closely with IT Security teams to guarantee the confidentiality and protection of sensitive data and regulatory compliance. Oversee Master Data Management (MDM), ensuring a Single Source of Truth for critical data assets. Data Platform Delivery and Operations Oversee the operation and Maintenance in Operational Condition (MOC/Run) of the Data environment, ensuring its performance and availability. Lead Data Engineering teams to build and maintain robust, efficient, and scalable data pipelines. Manage the portfolio of Data projects (Cloud migration, BI tool deployment, setting up Data Labs) within budget and timeline constraints. Support Analytics and Data Science teams in accessing and utilizing data for model creation and reporting. Leadership and Team Management Manage and develop the technical Data teams (Data Architects, Data Engineers, Data Modelers). Cultivate a data‑driven culture and technical excellence within the organization. Manage relationships with key Data Technology partners (software vendors, Cloud service providers). Requirements Master’s degree (or equivalent, e.g., Engineering School) in Computer Science, Data Science, or a related field. Minimum 10 to 12 years of experience in IT and Data, including at least 5 years in a Data leadership role (Chief Architect, Head of Data Engineering) at a large, Group‑level organization. Proven expertise in Data Distributed Systems Architecture (e.g., Hadoop, Spark, Kafka). Mastery of Cloud Data Warehousing solutions (e.g., Snowflake, Databricks, Google BigQuery, AWS Redshift, …). Strong knowledge of Data Governance, MDM, and Data Quality concepts. Significant experience in Data Modeling (Data Vault, Inmon, Kimball). Already fluent with GEN AI, Agentic AI, Machine Learning (ML) implications and Data Science infrastructure. Strategic Vision and the ability to translate complex business needs into data architecture solutions. Technical Leadership and strong managerial skills. Excellent communicator, capable of convincing Executive Management and motivating technical teams. Methodological Rigor and quality orientation. Ability to thrive in an international and matrix organizational environment. Fluent technical English is mandatory. Spanish and French nice to have. #J-18808-Ljbffr