Key Responsibilities:

📍Lead and mentor the data team to improve data accessibility and insights for both Front-Office and Middle-Office teams. 📍Drive the modernization of data development practices, leveraging modular, composable, and open-source technologies. 📍Oversee the creation of scalable, high-performance analytics platforms using cloud technologies to enhance analytical capabilities. 📍Support cross-functional teams in furthering insights related to funds, operations, and client intelligence. 📍Ensure compliance with data privacy policies and regulations. 📍Establish and maintain data standards, including business terms, definitions, code sets, data elements, and rules. 📍Improve data usability and availability, contributing to product strategies and roadmaps. 📍Facilitate data integration from third-party sources for research and mission-critical applications, ensuring repeatability and monitoring.

Qualifications:

📍At least 5 years of experience with Python for data automation, ETL/ELT processes in production environments (e.g., Airflow, Git, Medallion Architectures). 📍Proficiency with Snowflake (or Databricks) and DBT models in production. 📍Strong experience designing and leading transactional (OLTP) and analytical (OLAP) workload architectures. 📍Expertise in Pandas, Polars, Dask, and SQL. 📍Comfortable with Linux and Bash in a professional setting. 📍Experience using data replication technologies (e.g., Azure Data Factory, Qlik Replicate). 📍Familiarity with enterprise-level data visualization and reporting tools (e.g., Sigma, Tableau, Power BI).