Principal Data Engineer (Data Practice Lead)

Overview

In this role you will be the credible data voice for YLD in London, combining hands-on delivery with client leadership. You’ll help grow a data-first practice, shape proposals, and guide engagements while building your external reputation through events and writing. You’ll work cross-functionally with commercial and client services to translate client problems into robust data solutions. The opportunity centers on shaping data strategy and scalable pipelines in diverse client contexts.

Pay / Benefits

• Company Private Health care (Vitality)
• Enhanced maternity and paternity leave
• Company’s Pension Scheme
• 25 days annual holiday
• 2000 annual allowance for Training/Conferences
• 300 annual allowance for additional hardware Medical/tech equipment? (as stated)

Responsibilities

• Hands-on data engineering delivery: pipelines, transformations, models, and infrastructure
• Guide and unblock technical problems as the remit expands
• Define and evolve internal data standards (testing, documentation, code review)
• Mentor and grow data engineers across the company
• Join client meetings as the technical data authority alongside leadership
• Shaping proposals and pitches with a credible data approach
• Escalation point on live data engagements for technical judgment
• Travel for client workshops, discovery sessions, and external events
• Own growth of YLD’s data practice: capability, reputation, headcount
• Support sales to position data as a proactively sellable capability

Key requirements

• Strong data engineer or data lead with client-facing experience
• Experience leading a team or function
• Comfort presenting to senior stakeholders under commercial pressure
• Cross-functional fluency: translate engineering constraints into business terms
• Willingness to build public data presence over time
• Consulting or agency background is a strong plus but not essential if client exposure is proven

• Credible in front of clients and prospects
• Strong communication and negotiation skills
• Self-motivated with ownership mindset
• SQL proficiency with performance, cost, and planning knowledge
• Production-grade Python for data systems with typing and testing
• Data modeling: dimensional, Data Vault, normalised/denormalised trade-offs

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