Principal Data Engineer, Analytics

About Us DriveWealth is on a mission to make investing easier. We believe that everyone should have the ability to control their financial future, and that access to financial markets should not be limited by geography, wealth, or legacy systems. We are a global B2B financial technology organization dedicated to democratizing access to financial independence around the world. Our mission is realized through an API-based platform, empowering our partners to offer seamless investing and trading experiences to clients worldwide, all from their mobile devices. Our technology provides partners with a modern, extensible toolkit, enabling traditional investment workflows and innovative techniques like fractional share ownership. DriveWealth has evolved into a global platform offering trading of US equities, mutual funds, ETFs, fixed income, and options. There’s never been a better time to build a category-defining business and there has rarely been a team better positioned for this opportunity. Our culture blends the pace and agility of a fintech start-up with the impact, stability, and discipline of Wall Street. We encourage creativity and experimentation while ensuring institutional-grade execution and regulatory compliance in everything we do. Join us and help build the future of global investing! About the Role As a Principal Data Engineer, Analytics you will be dedicated to b [... source excerpt omitted ...] ur internal teams and partners to succeed. Your core focus will be on curating and maintaining key data sources and statistics that serve both internal and external stakeholders. You will act as the hands-on technical engine driving this work forward, spending 60–70% of your time writing code while shaping the architectural vision of our data ecosystem. You will architect for massive scale, treat data as software, and build highly performant, resilient models and reporting solutions (using Databricks, dbt, and Python) that fuel data-driven decision-making across the business. What You’ll Do Advanced Engineering & Coding End-to-End Ownership: Own the full lifecycle of data pro [... source excerpt omitted ...] x dbt models and data transformation logic for high-volume financial datasets (e.g., trade transactions, stock ledgers, and clearing/settlement records). Python Automation: Write production-grade Python scripts for advanced data processing, anomaly detection, and custom orchestration logic that SQL cannot handle alone. Performance Engineering: Take ownership of the "hardest problems" regarding query performance. Refactor legacy code and optimize incremental loading strategies to reduce costs and latency at scale. Technical Architecture & Standards CI/CD & DevOps: Own the technical implementation of our data deployment reporting pipelines (Git, dbt Cloud), ensuring robust versio