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DriveWealth is a global B2B fintech platform democratizing access to financial markets through an API-based infrastructure. The company enables partners to offer seamless investing and trading experiences worldwide, supporting US equities, mutual funds, ETFs, fixed income, and options trading.
As Principal Data Engineer, Analytics, you will lead the design and delivery of innovative data products that provide actionable insights to internal teams and external partners. This is a hands-on technical role where you'll spend 60–70% of your time writing code while shaping the architectural vision of the data ecosystem.
Key responsibilities include:
**Advanced Engineering & Coding**: Own the full lifecycle of data products from conceptualization through production deployment and optimization. Design and code complex dbt models and data transformation logic for high-volume financial datasets including trade transactions, stock ledgers, and clearing/settlement records. Write production-grade Python scripts for advanced data processing, anomaly detection, and custom orchestration. Take ownership of query performance optimization, refactoring legacy code, and optimizing incremental loading strategies to reduce costs and latency at scale.
**Technical Architecture & Standards**: Own CI/CD and DevOps implementation for data deployment and reporting pipelines using Git and dbt Cloud, ensuring robust version control and seamless integration. Engineer automated testing frameworks and validation suites using dbt tests and Python to ensure data integrity for critical business layers.
**Leadership & Cross-Functional Impact**: Act as the hands-on technical lead for major initiatives, scoping, designing, and managing complex data projects while remaining active in the codebase to ensure high-quality delivery. Mentor team members and establish best practices across the data organization.
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.
