Data Engineer

Who we are Conclusion Lifecycle is the Managed Services brand of Conclusion Iberia, focused on delivering long-term, scalable IT services across the full lifecycle, from build to run. It brings together the Managed Services operation that was previously part of Neotalent Conclusion, with a clearer focus on lifecycle ownership, operational excellence, and long-term partnerships. Conclusion Lifecycle also acts as the incubator for new lifecycle-based service offerings within Conclusion Iberia, supporting clients with sustainable, resilient, and continuously evolving digital solutions. Find out more about us at www.conclusionlifecycle.com. Role Overview We are looking for a Data Engineer to join one of our Nearshore Teams working remotely for international clients accross The Netherlands, Germany and other European countries. You will work throughout the data lifecycle, helping ensure that data platforms remain reliable, efficient and maintainable as business needs evolve. You will collaborate with technical teams and business stakeholders, contribute to engineering standards and automation practices, and share your knowledge with colleagues to continuously improve the quality of our data engineering services. What you will do - Design, build and maintain reliable and scalable data pipelines on Azure, AWS or Google Cloud Platform, predominantly using Databricks; - Develop and optimise batch and streaming data solutions capable of processing large volumes of data efficiently and accurately; - Translate functional and technical requirements into well-structured data models, using approaches such as 3NF, dimensional modelling and Data Vault; - Work with modern data platforms such as Databricks and Snowflake to deliver reliable, analytics-ready datasets; - Implement validation, monitoring and error-handling mechanisms to ensure data quality, consistency and availability; - Apply DevOps and CI/CD practices to automate testing, deployment and release processes for data solutions; - Collaborate with business stakeholders, analytics engineers and data scientists to support reporting, analytics and AI use cases; - Identify and implement opportunities for performance optimisation, cost efficiency and technical innovation; - Support the continuous improvement and automation of business and operational processes through data-driven solutions; - Share knowledge and engineering best practices within the team and support less experienced colleagues. What you are like - Experienced in Data Engineering, with a strong understanding of modern data platforms and architectures; - Highly proficient in SQL and/or Python for building and optimising data solutions; - Experienced with Databricks and/or Snowflake in data engineering environments; - Proficient in data modelling techniques such as 3NF, dimensional modelling and/or Data Vault; - Experienced with at least one major cloud platform: Microsoft Azure, AWS or Google Cloud Platform; - Proficient in DevOps and CI/CD practices, including automated testing, deployment and version control; - Knowledgeable about batch and/or streaming architectures, data quality, monitoring and scalable data processing; - Able to translate business requirements into effective and maintainable technical solutions; - Comfortable communicating and collaborating with both technical and non-technical stakeholders; - Proactive and quality-driven, with a focus on reliability, automation and continuous improvement; - Collaborative and willing to share knowledge and support the development of colleagues; - Excellent command of English, both spoken and written. Why join us - Work on challenging projects for big clients - Learn more about emerging technologies - Possibility of working remotely - Design your career plan - Access to continuous training and certifications - Evolve through our internal mobility program - … and much more!