Data Engineering Lead (AI)

TL;DR

Data Engineering Lead (AI): Building and stabilizing core data infrastructure and pipelines for an AI-native CRM platform with an accent on scalability, reliability, and data observability. Focus on shaping the long-term data architecture, defining technical standards, and enabling data-driven decision-making across product and go-to-market teams.

Location: Must be based in London (Hybrid, 3 days/week in Farringdon office)

Salary: £115,000 – £145,000

Company

hirify.global is an AI-native CRM platform designed for ambitious go-to-market teams, backed by top-tier investors including GV and Redpoint.

What you will do

• Design, build, and maintain reliable, scalable data pipelines and infrastructure.
• Improve the resilience, quality, and observability of the company's data platform.
• Partner with Product and Engineering to define the long-term evolution of data architecture.
• Create foundational datasets and transformations to support analytics and operational reporting.
• Operate as a senior technical leader, driving projects through ambiguity with high autonomy.
• Establish best practices, technical standards, and hiring plans for the growing data function.

Requirements

• Must be based in or able to commute to London for hybrid work.
• Deep hands-on experience designing and maintaining modern cloud-native data infrastructure.
• Strong proficiency in BigQuery, DBT, SQL, and Python (or equivalent ecosystems like Snowflake).
• Proven experience in a startup or scale-up environment balancing speed and technical quality.
• Ability to translate ambiguous business problems into precise technical implementations.
• Strong quantitative reasoning and experience supporting business-critical data infrastructure.

Culture & Benefits

• Competitive salary and equity in a high-growth tech company.
• 25 days of holiday plus local public holidays.
• Private medical insurance through AXA and pension contributions.
• Enhanced family leave policies.
• Regular team off-sites in international locations.
• Modern hardware and a collaborative, high-bar engineering culture.

Hiring process

• Introductory call with Talent and conversation with CTO & Co-Founder.
• Technical core interviews covering system architecture and data analysis.
• Final closing conversation with the CEO.