Data Architect – Lakehouse & Analytics

Description

Job Summary: Design and evolve the data architecture toward a modern, scalable, and governed lakehouse model, enabling analytics, machine learning, and AI as a strategic asset. Key Responsibilities: 1. Design modern and scalable data architecture 2. Enable analytics, machine learning, and AI 3. Transform data into a strategic asset for decision-making Design and evolve the data architecture, defining the transition to a modern, scalable, and governed lakehouse model. This model enables analytics, machine learning, and artificial intelligence, turning the data platform into a strategic asset for business decision-making. Responsibilities include designing patterns for data ingestion, transformation, modeling, consumption, and governance, ensuring coexistence of legacy and new environments such as Oracle DWH, Denodo, Cloudera, and Google Cloud Platform. Standards are established for data products, semantic layers, quality, lineage, security, and observability, with scalable and business-aligned solutions. The professional collaborates closely with business, analytics, engineering, and platform departments, participating in key technology decisions. We seek a candidate with strategic vision and pragmatism, capable of translating business needs into sound architectural decisions. This position is based in Elorrio. A degree in Computer Engineering, Business Analytics, Business Administration and Management, or Data Governance is required, along with solid experience in data architecture and complex analytical platforms. Experience with lakehouse environments, distributed processing, and hybrid on\-premise and cloud architectures is desirable. Knowledge of technologies such as Cloudera, Apache Iceberg, dbt, PySpark, SQL, Google Cloud Platform, Azure, Oracle DWH, and Denodo is required. Proficiency in data modeling, integration, governance, and security is essential. Experience in sectors such as retail, consumer goods, supply chain, pricing, customer loyalty, or e-commerce is valued, as well as familiarity with machine learning platforms, MLOps, generative AI, and approaches such as data products, data mesh, or federated governance.