Senior Engineer, Data Engineering

Hace 4 semanas

, España Talan Jornada completa
Company Description Talan – Positive Innovation Talan is an international consulting group specializing in innovation and business transformation through technology. Over the past 22 years, we’ve built a strong presence in the IT and consulting landscape, and we’re on track to reach €1 billion in revenue this year. Our Core Areas of Expertise
- Data & Technologies: We design and implement large-scale, end-to-end architecture and data solutions, including data integration, data science, visualization, Big Data, AI, and Generative AI.
- Cloud & Application Services: We integrate leading platforms such as SAP, Salesforce, Oracle, Microsoft, AWS, and IBM Maximo, helping clients transition to the cloud and improve operational efficiency.
- Management & Innovation Consulting: We lead business and digital transformation initiatives through project and change management best practices (PM, PMO, Agile, Scrum, Product Ownership), and support domains such as Supply Chain, Cybersecurity, and ESG/Low-Carbon strategies. We work with major global clients across diverse sectors, including Transport & Logistics, Financial Services, Energy & Utilities, Retail, and Media & Telecommunications. We are looking for an experienced Data Engineer to join a dynamic data engineering team and contribute to the development of modern, scalable data solutions within a Microsoft Azure and Databricks environment. You will play a key role in designing, developing and maintaining data pipelines and data platforms, working with large and complex datasets to support business intelligence, analytics and data-driven decision-making. This is an excellent opportunity for a Data Engineer who enjoys working with modern cloud technologies and is interested in data architecture, modelling and building robust data solutions.

Key Responsibilities
- Design, develop and maintain scalable data pipelines and ETL/ELT processes using Azure Data Factory (ADF) and Azure Databricks .
- Develop efficient data processing and transformation solutions using Python and Databricks.
- Work with large and complex datasets, ensuring data quality, reliability and performance.
- Contribute to the design and implementation of modern data architectures within the Azure ecosystem.
- Work with Medallion Architecture principles to build robust and scalable data solutions.
- Support the development of Data Vault and Business Vault architectures using Databricks on Azure.
- Work with Microsoft Fabric and OneLake , including the use of shortcuts to integrate and access data across different platforms.
- Contribute to data modelling activities within Azure Data Warehouse and related analytical environments.
- Collaborate with Data Architects, Developers, Analysts and other stakeholders to understand requirements and translate them into effective technical solutions.
- Identify opportunities to improve data processing, architecture, performance and automation.
- Ensure solutions follow best practices around scalability, security, maintainability and data governance. Must Requirements
- Experience creating data pipeline using python on Databricks
- Experience working at the curated and product layers of data engineering including transforming data into modelling technique including Data Vault 2. 0, Kimball (dimensional) and 3NF
- A good understanding of techniques to manage schema evolution, slowly changing dimensions, data harmonisation.