Lead Data Engineer
Listed on 2025-12-30
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IT/Tech
Data Engineer, Cloud Computing
Made Tech City Of Bristol, England, United Kingdom
Made Tech City Of Bristol, England, United Kingdom
6 days ago Be among the first 25 applicants
This range is provided by Made Tech. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay rangeDirect message the job poster from Made Tech
Founder at S.H.I.F.T | Leading the Shift in Talent Strategies and MindsetsAs a Lead Data Engineer or architect at Made Tech, you’ll play a pivotal role in helping public sector organisations become truly data‑lead, by equipping them with robust data platforms. You’ll also join a data team on its mission to get data knowledge and skills out of silos and embedded into delivery teams. You’ll also help implement efficient data pipelines & storage.
Keyresponsibilities
- Define, shape and perfect data strategies in central and local government.
- Help public sector teams understand the value of their data, and make the most of it.
- Establish yourself as a trusted advisor in data‑driven approaches using public cloud services like AWS, Azure and GCP.
- As employee growth is a huge focus here, we would expect you to contribute to our recruitment efforts and take on line management responsibilities.
We are looking for candidates with a range of skills and experience, please apply even if you don’t meet all the criteria as if unsuccessful we can provide you with feedback.
- Proficiency in Git (inc. Github Actions) and able to explain the benefits of different branch strategies.
- Strong experience in IaC and able to guide how one could deploy infrastructure into different environments.
- Knowledge of handling and transforming various data types (JSON, CSV, etc) with Apache Spark, Databricks or Hadoop.
- Good understanding of possible architectures involved in modern data system design (Data Warehouse, Data Lakes, Data Meshes)
- Ability to create data pipelines on a cloud environment and integrate error handling within these pipelines.
- You understand how to create reusable libraries to encourage uniformity or approach across multiple data pipelines.
- Able to document and present end‑to‑end diagrams to explain a data processing system on a cloud environment.
- Some knowledge of how you would present diagrams (C4, UML, etc.)
- Enthusiasm for learning and self‑development.
- You have experience of working on agile delivery‑lead projects and can apply agile practices such as Scrum, XP, Kanban.
- Can own the cloud infrastructure underpinning data systems through a Dev Ops approach.
- Design and implement efficient data transformation processes at scale, both in batch and streaming use cases.
- You are a skilled Data Engineer who has delivered data platforms.
- Knowledge of SOLID, DRY and TDD principles and how to practically implement these into a project.
- You can demonstrate a commercial mindset when on projects to grow accounts organically with senior stakeholders.
- You have the experience to improve resilience into a project by checking for software vulnerabilities and implement appropriate testing strategies (unit integration, data quality, etc)
- You are skilled at offering guidance on how one would implement a robust Dev Ops approach in a data project.
- You can comfortably talk about tools needed such as Data Ops in areas such as orchestration, data integration and data analytics.
- Working at a technology consultancy
- Working with Docker and virtual environments as part of the development and CI/CD process.
- Working with senior stakeholders to gather requirements and keep them engaged with
- Experience in working with a team of engineers using a variety of techniques such as pair programming or mob programming.
- Working with data scientists to product ionise advanced data deliverables, such as machine learning models
- Working knowledge of statistics
- Working with multidisciplinary digital and technology teams
- Working within the public sector
- Working with data scientists to product ionise advanced data deliverables, such as machine learning models
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