Data Engineering Manager, Not On The High Street

• An experienced data engineer comfortable leading both technical architecture and team development
• Equally effective in writing production code and mentoring engineers with a hands-on leadership style
• Respected for translating complex business needs into scalable technical solutions
• Committed to agile practices, continuous learning and cross-functional collaboration
• Expert Python and SQL skills with proven performance optimisation experience in production environments
• Strong AWS expertise in designing and implementing cloud-native data architectures
• Extensive ETL/ELT pipeline development, managing complex data workflows and transformations
• Data warehouse experience, preferably Snowflake or BigQuery, with advanced modelling capabilities
• Docker containerisation knowledge and test-driven development practices
• Experience with Orchestration tools like Airflow or Dagster
• Advanced dbt experience, including the use of custom macros and complex incremental models
• Proven ability in mentoring technical talent and developing high-performing engineering teams
• Strong stakeholder management skills, working effectively across business functions
• Experience translating business needs into technical roadmaps and architectural decisions
• Excellent communication skills, influencing technical and non-technical stakeholders
• Don’t meet every single requirement? No problem. Your strengths, passion & fresh perspective could be just what we’re looking for - so we encourage you to apply!

Desirable

• In the role of our Data Engineering Manager, you'll be a hands-on technical leader driving our data infrastructure strategy
• You'll own the complete data engineering stack whilst supporting a focused team of 3 engineers and data scientists
• This position offers significant technical authority and business impact, shaping how data powers our marketplace decisions and customer experiences
• Our current stack includes: Snowflake, dbt, Airflow, AWS, Stitch, Looker and Count
• Own the complete data engineering stack, from pipelines through to platform architecture and BI tools
• Design marketplace-focused data models enabling rapid experimentation and reliable insights
• Build robust ETL/ELT pipelines managing large-scale datasets with exceptional performance standards
• Ensure data quality, reliability and system performance across all infrastructure
• Support and develop 3 data engineers and data scientists through mentoring and technical guidance
• Foster a technical excellence culture, promoting continuous learning and best practices
• Drive agile delivery methods, ensuring iterative improvement and consistent value delivery
• Collaborate with the Analytics team, delivering infrastructure supporting actionable business insights
• Enable self-service data access, empowering product and commercial teams with direct data control
• Support machine learning initiatives through scalable data foundations and robust architecture
• Transform business requirements into technical solutions, driving measurable customer outcomes

• Our recruitment processes are fully remote, taking advantage of the wonders of modern-day technology
• Applied
• Introductory Call
• You'll speak with a member of the hiring team about the role in more detail, and get the opportunity to ask any questions about the role or Not On The High Street in general!
• Team Interview
• You'll speak with some of the team that you'll be working with to discuss your skills and experience in further detail
• Task
• We'll ask you to complete a technical task to give you a chance to showcase your skills and knowledge
• Technical & Community Interview
• We'll get together and talk through your technical task to get a better idea of your skills in practice. You'll also speak with some NOTHS-ers from different teams across the business so that we can get to know more about you!
• Hired