Senior Data Engineer

Our Senior Data Engineers enable public sector organisations to embrace a data-driven approach by providing data platforms and services that are high-quality, cost-efficient, and tailored to clients’ needs. They develop, operate, and maintain these services. They make sure they provide maximum value to data consumers, including analysts, scientists, and business stakeholders. At Made Tech we want to positively impact the future of the country by using technology to improve society, for everyone. We want to empower the public sector to deliver and continuously improve digital services that are user-centric, data-driven and freed from legacy technology. A key component of this is developing modern data systems and platforms that drive informed decision-making for our clients. As a Senior Data Engineer, your day to day tasks and role may vary according to our clients' needs. The role is very hands-on and you'll support as a senior contributor for a project, focusing on both delivering engineering work as well as upskilling members of the client team. You’ll need to have a drive to deliver outcomes for users. You’ll make sure that the wider context of a delivery is considered and maintain alignment between the operational and analytical aspects of the engineering solution. As a member of the Data and AI Practice within Made Tech, you will also participate in the continued development of the practice, as well as representing us both internally to the organisation and publicly via presentations. You’ll need to have a drive to deliver outcomes for users and have a desire to share your knowledge and participate in skill transfer sessions. We are looking for candidates with a range of skills and experience, please apply even if you don’t meet all the criteria. Engineering and Data Engineering Hands-on and knowledge of programming languages particularly Python Practical experience with major cloud providers including GCP, Azure, or AWS Knowledge of core software engineering concepts like DRY and SOLID Proficiency in version control systems, specifically Git or similar tools Demonstrated application of TDD and diverse testing methodologies, such as data quality, integration, and unit testing Ability to leverage CI/CD pipelines to maintain code quality and facilitate deployments Knowledge of Data Engineering fundamentals, including Batch/Streaming and ETL/ELT Familiarity with various data architectures, such as Lakes and Warehouses Hands-on experience with data cleansing and transformation within unified, standardised schemas Technologies While mastery of every tool is not required, we are seeking Engineers who have experience with one or more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and…