About us: Seriös Group are a fast-growing UK-based tech start-up specialising in delivery of innovative high quality data solutions. Our mission is to empower organisations to take control of their data, delivering rapid value to enterprise-level clients without compromise, while building a proprietary data platform framework (Seriös ONE) to transform how businesses manage and leverage data. Our dynamic, collaborative team thrives on delivering exceptional results for our clients and driving innovation in the data space. Role overview: We are looking for ambitious Data Engineers at all levels to play a crucial role in helping us design, build, and maintain robust data pipelines and infrastructure. You will collaborate with cross-functional teams to ensure efficient data processing, storage, and accessibility. This is a fantastic opportunity to work on industry-leading best practices in data engineering while gaining hands-on experience with cutting-edge technologies in cloud environments. You will have opportunities to work on bespoke customer deliveries as well as our Seriös ONE suite of data platform products. Key Responsibilities: Design, build, and maintain scalable and efficient data pipelines and ETL processes. Implement data engineering best practices and methodologies, ensuring data integrity, security, and quality. Develop and maintain data models using both Data Vault and Kimball methodologies to support analytical and operational use cases. Work with structured and unstructured data sources, transforming them into valuable business insights. Develop, test, and deploy code using Python and other relevant technologies. Optimise data storage and retrieval solutions to ensure high performance and cost efficiency. Collaborate with data architects, data engineers, and test engineers to ensure high quality seamless integration of our data solutions. Deploy and manage data infrastructure in cloud environments, including AWS, Azure, GCP, Oracle, Databricks, or Snowflake. Continuously evaluate and adopt emerging technologies and tools to improve data engineering processes. The above list is non-exhaustive; you may be required to carry out any ancillary duties in relation to your role, in addition to the abovementioned list. Requirements: Experience: Previous experience in a data engineering role within a cloud-based environment. Proven track record of implementing data engineering best practices and methodologies. Experience working with both structured and unstructured data at scale. Technical Skills: Strong experience with Python for data processing and automation. Hands-on experience with cloud data platforms such as AWS, Azure, GCP, Oracle, Databricks, or Snowflake. Solid understanding and practical application of Data Vault and Kimball data modelling methodologies. Proficiency in SQL for data manipulation, transformation, and querying. Experience designing and optimising ETL/ELT workflows for large-scale data processing. Knowledge of CI/CD pipelines, version control, and DevOps practices related to data engineering. Strong understanding of data governance, data security, and compliance best practices. Person Specification: Problem-solving mindset with the ability to design scalable solutions for complex data challenges. Ability to work independently as well as collaborate effectively within a team. Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders, with a consultative approach. Strong organisational skills and attention to detail. The Employer reserves the right to make amends to the job specification from time to time, to meet the needs of the business. Please note: This vacancy covers the full range and breadth of skills and experience. Suitable level for entry will be discussed at interview.