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Company Description Talan – Positive Innovation Talan is an international consulting group specializing in innovation and business transformation through technology. With over 7,200 consultants in 21 countries and a turnover of €850M, we are committed to delivering impactful, future-ready solutions. Talan at a Glance Headquartered in Paris and operating globally, Talan combines technology, innovation, and empowerment to deliver measurable results for our clients. 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. Practical experience of using DABs (Declarative Automation Bundles, nee Databricks Asset Bundles) for deployment Practical experience using git repositories and CI/CD pipelines (preferably with GitHub and ADO) Practical experience developing pipeline in a IDE environment (Preferably with VSCode) Nice to Have Experience with Microsoft Fabric and OneLake , particularly OneLake shortcuts. Knowledge of data modelling in Azure Data Warehouse . Experience working within the financial services or wealth management sector . Familiarity with data governance, data quality and modern cloud data architecture principles. What do we offer you? Remote within Spain Time zone. Possibility to be part of a multicultural team and work on international projects. CET working hours If you have read this far and you are looking forward to joining this challenge, do not hesitate to apply... we would be delighted to meet you! Talan Spain’s commitment to non-discrimination based on gender, race, ideology, or any other reason, in accordance with the company’s "Equality Plan" and the current regulations on gender equality between women and men (Royal Decree-Law 6/2019).
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
