Overview

As 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 join a data team on its mission to remove data silos and embed data knowledge and skills into delivery teams. You\'ll also help implement efficient data pipelines and storage.

Responsibilities

• Define, shape and refine data strategies in central and local government.
• Help public sector teams understand the value of their data and maximise its use.
• Establish yourself as a trusted advisor in data driven approaches using public cloud services such as AWS, Azure and GCP.
• Contribute to recruitment efforts and take on line management responsibilities as the team grows.
• Support a culture of inclusion and diversity, and engage with communities of practice and employee networks where available.

Benefits and Culture

• Flexible benefit platform including a Smart Tech scheme, Cycle to work scheme, and an individual benefits allowance (healthcare cash plan or pension).
• 30 days holiday; flexible working hours; flexible parental leave options.
• Remote working options for all staff; paid counselling and access to financial and legal advice.
• Optional social and wellbeing calendar of events to support connection and wellbeing.
• Slack-based community with dedicated channels for communities, allies, and COPs; opportunities to learn and grow within the company.

Eligibility

We require eligibility for SC (security check) clearance for projects where required. Eligibility for SC requires 5 years\' UK residency and 5 years\' employment history (or back to full-time education). If it becomes apparent at any point in the interview process that you may not be eligible for SC, we will not progress your application and will inform you of the reason.

Hiring Process

1. Talent team review of applications; AI may be used to assist speed, but a human will make final decisions.
2. Shortlisted applicants are invited to a screening call (25–30 minutes).
3. Interviews with the hiring manager and/or team members (initial virtual interview, ~45–60 minutes).
4. Final stage interview (usually with two team members; typically ~1 hour).

Qualifications

• Proficiency in Git (including GitHub Actions) and ability to explain benefits of different branching strategies.
• Strong experience in Infrastructure as Code (IaC) and deploying infrastructure across environments.
• Knowledge of handling and transforming data types (JSON, CSV, etc.) with Apache Spark, Databricks or Hadoop.
• Good understanding of modern data architectures (Data Warehouse, Data Lakes, Data Mesh).
• Ability to create data pipelines on a cloud environment with robust error handling.
• Experience creating reusable libraries to promote consistency across data pipelines.
• Ability to document and present end-to-end diagrams explaining data processing on cloud platforms (C4, UML, etc.).
• Enthusiasm for learning and self-development.
• Experience working on agile delivery projects and applying practices such as Scrum, XP, Kanban.
• Ability to own cloud infrastructure underpinning data systems using a DevOps approach.
• Design and implement efficient data transformation processes at scale (batch and streaming).
• Proven experience delivering data platforms as a Data Engineer.
• Knowledge of SOLID, DRY and TDD principles and how to apply them in projects.
• Commercial mindset to grow accounts with senior stakeholders.
• Experience improving resilience by assessing software vulnerabilities and implementing testing strategies (unit, integration, data quality, etc.).
• Ability to guide on robust DevOps practices in data projects and discuss tools such as DataOps for orchestration, data integration and analytics.

Desirable Experience

• Experience working in a technology consultancy.
• Experience with Docker and virtual environments in development and CI/CD.
• Experience working with senior stakeholders to gather and maintain engagement.
• Experience working with engineers using pair programming or mob programming.
• Experience productionising advanced data deliverables with data scientists (e.g., ML models).
• Working knowledge of statistics.
• Experience working with multidisciplinary digital and technology teams.
• Experience working in the public sector.