Lead Data Engineer

Who We Are

NEXT Ventures is where ambition takes shape and movement becomes momentum. As a global platform revolutionising access to performance-based capital, we empower the world’s most driven individuals to rise. Through our flagship brand, FundedNext, we empower dreamers to become doers, and potential to turn into performance. With 500+ driven minds across five countries, we power a global rhythm—220,000+ daily users from 170+ nations, each chasing greatness in their own way.

Your Role in Our Mission

As Lead Data Engineer at NEXT Ventures, you'll own the data platform that powers every major decision—turning high-volume trading and product data into reliable, analytics-ready truth that drives revenue reporting, trader analytics, surveillance, and AI. This is a build-from-scratch mandate: you'll inherit terabytes across multiple products and a team hungry for senior leadership, then architect the full stack from source ingestion to warehouse, take pipelines from zero to production, and set the standard for how data engineering is done here. You'll also do it the modern way—working inside AI-assisted environments (Claude, Claude Code, MCP) to ship in a day what once took a week. If you treat AI as a force multiplier and can raise an entire team's bar on how it's used, this role is for you.

How You’ll Make an ImpactBuild the Cloud Data Platform

• Architect and scale the end-to-end cloud data platform: source ingestion, transformation, warehouse, and the monitoring and quality layers that keep it trustworthy

• Lead the transition from batch-oriented systems to a scalable AWS-based streaming architecture

• Design and implement real-time data replication pipelines across MySQL, PostgreSQL, and Amazon Redshift for core products hosted in the cloud

• Work with high-volume, terabyte-scale data across NEXT's products, building for the scale we'll reach in three years, not just today

• Ensure scalability, security, cost-efficiency, and performance in every data solution you ship

AI-Powered Engineering and Productivity

• Work daily within AI-assisted development setups (Claude, Claude Code, and similar tools) to accelerate design, coding, debugging, and documentation, delivering critical work at 5 to 7x traditional speed

• Build and maintain MCP (Model Context Protocol) servers that connect our data systems (warehouses, dashboards, internal APIs) to AI assistants

• Develop AI-powered dashboards and analytics experiences: natural-language querying, automated insight generation, and LLM-driven reporting layers

• Apply prompt engineering and LLM API integration (Anthropic/Claude API or similar) to automate repetitive data engineering tasks such as pipeline scaffolding, schema documentation, data quality checks, and runbook generation