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Ravio in London is seeking a Lead Data Engineer to lead a small data team, staying hands-on while designing, building, and operating data systems behind our compensation benchmarks and AI tools.
You’ll combine technical leadership with coaching, shaping the data roadmap with Product, Data Science and Insights, and delivering reliable, value-focused outcomes in a fast-paced startup.
Remote-friendly, flexible working with ownership in Ravio’s mission to help people get paid fairly.
We’re looking for a Lead Data Engineer to lead a small team of data engineers within our Engineering team. You’ll remain hands-on in designing, building, and operating the data systems behind our compensation benchmarks, customer-facing tools, and AI agents. You’ll take a platform engineering approach to data, building reliable, reusable capabilities that help Engineering, Data Science, and Insights deliver. You’ll combine technical leadership with line management and coaching, working with engineering and product colleagues to turn priorities into delivered outcomes.
Be a senior technical contributor, building and operating the pipelines, integrations, and data services behind Ravio’s product. Design clear interfaces between ingestion, transformation, and downstream applications so teams can build on trusted data without bespoke support for every change. Shape and deliver the data roadmap with Product, Data Science, and Insights. Prioritise improvements that deliver customer value, reduce recurring manual work, or address reliability needs, while keeping complexity and cloud costs under control. Build data quality, governance, and security into everyday delivery through automated checks, clear data ownership, and appropriate access controls. Work with engineering colleagues to integrate data systems into shared development, deployment, and monitoring practices. Use version-controlled transformations, automated tests, and repeatable deployments, reducing bespoke tooling where it adds unnecessary overhead. Own the reliability and day‑to‑day support of the team’s production data systems, improving monitoring and recovery. Build reusable ingestion patterns and self‑service workflows around recurring needs, measuring their value through faster delivery, fewer failures, and less manual support. Use AI‑assisted tools for development, testing, documentation, and investigation. Help the team use them effectively, with appropriate review of outputs and protection of customer data. Lead the team’s delivery planning and ways of working, keeping priorities, scope, and dependencies visible. Take part in shared product prioritisation, bringing requests from Data Science, Insights, and Operations into an agreed delivery plan. Partner with software engineers, product managers, and data colleagues to make timely decisions and share responsibility for delivered outcomes. Line manage and coach a small team of data engineers, providing regular feedback and supporting their technical and career development. Build a supportive, accountable team with shared ownership of its systems. Use pairing, code reviews, documentation, and operational handovers to spread knowledge.
Six-plus years’ experience in data engineering, with at least two years in a team leadership role. Strong Python and SQL skills, with experience building and operating production data systems. Experience with data modelling, transformation frameworks such as dbt, and workflow orchestration. Experience applying platform engineering principles to data systems, such as reusable ingestion patterns, clear data interfaces, or self‑service tooling that other teams use successfully. Experience with cloud infrastructure, infrastructure as code, automated testing, and continuous integration and delivery (CI/CD). Practical understanding of reliable data processing, including schema changes, retries, safe reprocessing, and backfills. Experience using monitoring and data quality checks to investigate failures and improve reliability. Practical use of AI‑assisted engineering tools, with sound judgement about verification, security, and where automation adds value. Proven ability to mentor engineers, set team goals, and deliver value for users and the business. Comfortable working in a fast‑paced startup environment with a bias for action. Excellent listening and communication skills. You speak the language of engineers and data scientists, and are comfortable working with Product, Customer Success, Operations, and founders. You bring empathy and strong social and emotional intelligence, with an ability to put yourself in others’ shoes. You take satisfaction in solving challenging problems and helping a talented team deliver effectively.
Opportunity to be a critical team member in a high‑growth startup. A blend of hands‑on engineering and leadership, giving you both direct impact and career growth. Remote‑friendly, flexible work culture with a high degree of ownership. Work on meaningful problems that help people get paid fairly and competitively in their careers.