Principal Data Engineer, Analytics

DriveWealth is a global B2B financial technology organization that provides an API-based platform for investing and trading. The Principal Data Engineer, Analytics will build and maintain scalable data products, models, and reporting solutions using Databricks, dbt, and Python, while leading architecture, performance optimization, data quality, and cross-functional delivery.

Responsibilities:

• End-to-End Ownership: Own the full lifecycle of data products, from initial conceptualization and architecture through to production deployment, optimization, and maintenance
• Core Development: Design and code complex 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
• CI/CD & DevOps: Own the technical implementation of our data deployment reporting pipelines (Git, dbt Cloud), ensuring robust version control and seamless integration
• Data Quality as Code: Engineer automated testing frameworks and validation suites (using dbt tests/Python) to ensure data integrity for critical business layers
• Technical Project Leadership: Act as the hands-on lead for major initiatives. Scope, design, and manage complex data projects while remaining active in the codebase to ensure high-quality delivery
• Cross-Functional Partnership: Partner directly with stakeholders across Product, Finance, Operations, Risk, and Trading to translate domain-specific requirements into robust data products and reporting solutions
• Mentorship & Guidance: Act as the "go-to" technical resource for the team. Conduct thorough code reviews and help senior and junior engineers solve blockers through pair programming and architectural guidance

Requirements:

• 8+ years of professional experience in analytics engineering or data engineering, with a proven track record of building and scaling analytical data ecosystems
• Expert proficiency in SQL, with experience optimizing complex queries and data models at scale
• Advanced proficiency in Python for data manipulation (Pandas/Polars/Spark) and interaction with APIs/AWS services
• Experience using Databricks for analytics workloads, including building and optimizing data models using Databricks SQL and dbt
• Experience with dbt materializations, macros, and package management
• Experience architecting data models for FinTech and Capital Markets, including trade lifecycles, clearing/settlement, risk models, and financial reporting
• AI-Assisted Engineering: Proficiency in leveraging AI tools (e.g., GitHub Copilot,or similar LLMs) to accelerate code delivery, automate documentation, and optimize engineering workflows
• Proven ability to build data solutions that are reusable and modular, rather than one-off scripts
• Experience treating data as software by implementing unit testing, CI/CD, comprehensive documentation, and SLA monitoring
• Ability to independently diagnose and resolve complex errors or issues within distributed systems (Spark/Databricks)
• Bachelor's degree in Computer Science, Software Engineering, or a related technical field
• This role is open to candidates in the following locations: New York City, Chicago, Austin, Dallas, Denver, Miami, San Francisco Bay Area, or Seattle
• If based in New York or Chicago: This role is expected to come into the office 3 days a week on a cadence set by the Hiring Manager/Team
• If based in Austin, Dallas, Denver, Miami, San Francisco, or Seattle: This is a fully remote role, though you may need to visit our onsite offices from time to time
• If you're not based in one of the locations listed above, this role is not a fit, and we cannot accommodate remote work outside these locations
• Applicants must be authorized to work for any employer in the U.S. DriveWealth does not sponsor or take over sponsorship of an employment visa at this time
• Applicants must possess the legal right to work in the country where the position is located at the time of application
• For US-based roles: Applicants must be currently authorized to work in the United States on a full-time basis without the need for current or future visa sponsorship. DriveWealth does not provide visa sponsorship or support for employment authorization, including transfers, at this time. Offers of employment are strictly contingent upon an individual's ability to secure and maintain the legal right to work at the Company
• Experience implementing Airflow or similar orchestrators
• Experience with Sigma Computing (from a data modeling perspective)
• Experience building Data Apps within Databricks
• Experience using AI/LLM tools to enable faster, smarter analytics workflows