Lead the design, architecture, and implementation of scalable and reliable data pipelines that serve as the foundation for all analytics, from BI dashboards to production ML/AI models.
Take ownership of our core data systems, including our cloud data warehouse, ETL/ELT orchestration, and real-time data processing capabilities.
Teach, mentor, and oversee less-experienced engineers, establishing best practices for code quality, testing, and operational excellence.
Partner closely with Quantitative Researchers, ML Engineers, and business stakeholders to translate their needs into robust, production-grade data solutions.
Establish and enforce data quality, governance, and observability standards across all data products to ensure their reliability and build trust with all consumers of data.
Requirements
7+ years of hands-on experience designing, building, and productionizing data-intensive systems.
Demonstrated experience mentoring junior engineers and leading complex technical projects.
Expert-level proficiency in SQL and Python, with deep knowledge of data manipulation libraries and backend development patterns.
Proven track record of architecting, building, and owning mission-critical data systems in a production environment (e.g., data warehouses, data lakes, ETL/ELT pipelines).
Deep experience with modern batch data processing and orchestration frameworks (e.g., Airflow, Dagster, Prefect).
Experience with real-time data processing and messaging systems (e.g., Apache Kafka, GCP Pub/Sub).