Data Engineering, Director

About the Role

We are seeking a Data Architect & Engineering Lead to drive the strategy and execution of our next-generation data platform. This leader will design, implement, and manage highly scalable, high-performance data systems that power our core investment and analytical capabilities. The ideal candidate has deep expertise in distributed systems, modern cloud data architectures, and a proven track record of leading high-impact engineering teams, particularly within the financial or capital markets sector.

Responsibilities

• Lead and mentor a distributed team of data and platform engineers, fostering a culture of technical excellence, accountability, and professional growth.
• Oversee the design and implementation of ETL/ELT pipelines using cloud data warehouses like Snowflake, ensuring data quality and compliance for multi-terabyte scale data stores.
• Drive the integration of advanced data science workflows, leveraging cloud-native ML services to enhance predictive models and analytical dashboards.
• Partner with investment, risk, and product teams to translate complex business requirements into high-performance database solutions.
• Guide best practices for cloud infrastructure (Azure or AWS) and containerized data services (Enterprise-grade container orchestration platform supporting declarative infrastructure and horizontal scaling, Snowpark Container Services).
• Lead deep-dive post-mortem analysis and provide architectural solutions for highly complex database issues.
• Manage database objects such as schemas, tables, indexes, triggers, and views.
• Ensure high availability, reliability, and data integrity of databases.
• Perform regular database maintenance and health checks.
• Support production databases and resolve data-related incidents.
• Monitor database performance and system health.
• Identify and resolve performance bottlenecks.
• Tune SQL queries, indexes, and database configurations.
• Assist development teams with query optimization and schema design.
• Maintain documentation for database configurations and procedures.

Requirements

• 15+ years of progressive experience in Data Engineering, Database Architecture, and Distributed Systems, with significant time spent in a technical lead role.
• Proven expertise in modern data warehousing technologies, specifically Snowflake.
• Hands-on experience managing a variety of database flavors (OLTP, cloud-native data warehouses, distributed column stores) and query engines at massive scale.
• Strong background in cloud infrastructure and services, either AWS or Azure.
• Demonstrated ability in database design, SQL tuning, and query optimization for both OLTP and OLAP systems.
• Strong expertise in writing complex SQL and Python.
• Experience building analytics with full-stack data science and data visualization tooling like NumPy, Pandas, Matplotlib, and Streamlit.
• Knowledge and experience working in classical or modern machine learning projects (preferred but not necessary).
• Experience closely working with ML Engineers.
• Master’s or Bachelor’s in Computer Science, Math, or Statistics.
• Strong expertise in PostgreSQL architecture and internals.
• Advanced knowledge of SQL and PL/pgSQL.
• Experience with performance tuning and monitoring tools.
• Familiarity with Linux/Unix environments.
• Scripting skills (Bash, Python, or similar).

Benefits

• Strong retirement plan.
• Tuition reimbursement.
• Comprehensive healthcare.
• Support for working parents.
• Flexible Time Off (FTO) to relax, recharge, and be there for the people you care about.

Schedule

Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities.