Ofertas de empleo de interim management en Barcelona

Overview This newly established position is designed to optimise data ownership and accountability, as well as the management of data models. The role encompasses designing and maintaining data models for transactional and analytical data stores, administering operational databases, and supporting advanced analytical workloads across cloud platforms. Additionally, it involves global oversight as an account administrator for Databricks environments. Key Responsibilities * Develop new, or update existing, conceptual, logical, and physical data models as required to support core business applications and analytical tasks. * Administer relational databases such as Oracle, PostgreSQL, SQL Server, or MySQL to maximise reliability, performance, and data resilience. * Manage NoSQL databases and Databricks Delta Lake models for analytical workloads. * Execute performance tuning activities at the database, pipeline, and data model levels, including indexing, partitioning, caching, and compute scaling. * Oversee security and compliance standards, such as IAM roles, encryption policies, auditing, and implementation of least-privilege access protocols. * Assist with backup and disaster recovery planning to ensure business continuity within cloud environments.

Description A vacancy has arisen within the Data Governance team for a Senior Technical Data Analyst. This position will be responsible for supporting both Data Catalog and Master Data Management (MDM) initiatives, ensuring the application and adoption of data governance standards and data security protocols across the organization. Key Responsibilities * Lead MDM implementation efforts, including designing data acquisition, cleansing, and matching rules to generate golden records. * Develop mechanisms for sharing golden records with upstream and downstream applications. * Oversee the implementation and ongoing maintenance of a data catalog, ensuring regular updates and alignment with organizational objectives. * Define and enforce data classification rules across various systems and data sources. * Compile and manage a comprehensive Business Glossary derived from existing documentation and organizational data analysis. * Analyze diverse datasets to identify Critical Data Elements (CDEs). * Collaborate cross-functionally with technical and business teams to foster best practices in data governance and promote their consistent adoption. * Document processes, standards, and data rules to ensure clear communication and accessibility for all stakeholders.

The Data Governance team is seeking to appoint a DevOps Engineer to support ongoing project implementation efforts. We require a professional with proven experience in CI/CD pipelines, Terraform DevOps methodologies, and ideally proficiency in Python and REST APIs. Key Responsibilities * Collaborate in the development and optimisation of data pipelines employing DevOps best practices, including continuous integration/continuous deployment (CI/CD), automation, and containerisation. * Support deployment activities, provide technical assistance, and conduct troubleshooting during implementation phases. * Identify opportunities for workflow improvement and optimise existing processes. * Develop and maintain Python scripts supporting data integration, transformation, and analysis. * Consume, validate, and document both internal and external REST APIs.

We are looking for an experienced Senior Data Scientist to join a high-impact project in Barcelona. If you have a strong background in machine learning, predictive modeling, and AI-driven solutions, and are looking for Contract Freelancing opportunities in a multinational environment, this role is for you! What You’ll Do Collaborate with stakeholders to define business challenges and create data-driven solutions. Apply machine learning and predictive modeling to extract valuable insights. Guide suppliers in implementing AI/ML solutions using Microsoft Cognitive Services, OpenAI, and Azure ML. Develop algorithms and models to optimize processes and improve product performance. Work closely with Data Ambassadors and the Data Center of Excellence (CoE) to ensure project success. Continuously evaluate and refine models with A/B testing and monitoring techniques.