Data Team Leader (Fintech)

TL;DR

Data Team Leader (Fintech): Leading a team of data engineers to build and maintain scalable data infrastructure and pipelines with an accent on data quality, governance, and architecture. Focus on designing production-grade AI applications, optimizing LLM workflows, and driving data-driven practices across the R&D organization.

Location: Must be based in London or able to work in a hybrid capacity from the London office.

Company

hirify.global is a fintech company providing Securities Lending as a Service (SLaaS) to automate and democratize capital markets for brokers and wealth managers.

What you will do

• Lead, mentor, and grow a team of data engineers while fostering a culture of technical excellence.
• Define and drive data architecture strategy, including scalable pipelines, ETL workflows, and data lake expansion.
• Own data quality, integrity, and validation standards across the organization.
• Partner with R&D and business teams to translate data needs into robust, scalable solutions.
• Lead the design and optimization of AI prompts and data-driven applications, including autonomous agents.
• Collaborate effectively across distributed, international R&D teams.

Requirements

• Must be based in or able to work from London.
• Bachelor’s or Master’s degree in Computer Science or a related field.
• 5+ years of experience in Data Engineering, with at least 2 years in a leadership role.
• Deep expertise in SQL, data modeling, and governance concepts.
• Hands-on experience with Databricks, Azure, and modern analytics tools like Spark.
• Proven experience building production-grade AI applications, including LLMs and prompt design.

Nice to have

• Previous experience as a DBA.
• Experience with NoSQL databases.
• Ability to prototype and validate ideas quickly through Proof of Concepts.

Culture & Benefits

• Opportunity to work on a mission to democratize capital markets.
• Collaborative environment within an international R&D organization.
• Focus on innovation in AI-native capabilities and autonomous data workflows.
• Hybrid work model balancing office collaboration and flexibility.