Boston, MA (Hybrid)

• Lead the strategy, architecture, and delivery of enterprise data and analytics platforms that support investment research, portfolio management, and business intelligence initiatives.
• Partner closely with investment professionals, quantitative researchers, product teams, and business stakeholders to deliver technology-driven solutions that improve investment decision-making.
• Serve as a hands-on technical leader, driving architecture, design, and engineering excellence while developing and mentoring a high-performing team.

• Design, build, and scale modern cloud-based data platforms supporting investment and analytics workflows.
• Develop and maintain robust batch and near real-time data pipelines for financial, economic, and alternative datasets.
• Establish best practices for data modeling, governance, data quality, observability, testing, and platform reliability.
• Lead architecture decisions and provide technical guidance for complex, business-critical initiatives.
• Partner with investment and research teams to identify opportunities for automation, analytics, and operational improvement.
• Build scalable infrastructure and platforms that support data-intensive investment processes.
• Drive continuous improvement across engineering processes, delivery standards, and platform performance.
• Lead, mentor, and develop engineering talent, fostering a culture of accountability, ownership, and collaboration.
• Manage cross-functional initiatives and coordinate with product, operations, and business teams to ensure successful execution.
• Solve complex and often unstructured business problems through innovative technology solutions.

• 10+ years of experience in data engineering, software engineering, and technology delivery.
• 5+ years of experience leading technical projects, engineering teams, or large-scale platform initiatives.
• Strong experience designing and operating enterprise-scale cloud data platforms.
• Advanced proficiency with SQL and Python.
• Hands-on experience with Snowflake or comparable cloud data warehouse technologies.
• Experience with DBT, Airflow, Dagster, or similar data orchestration and transformation tools.
• Deep understanding of ETL/ELT development, data modeling, data governance, data quality, observability, and performance optimization.
• Proven track record of leading engineering teams and delivering data and analytics platforms from design through production.
• Strong communication skills with the ability to interact effectively with both technical and business stakeholders.
• Experience driving architecture strategy, platform modernization, and engineering best practices.

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• Master's degree preferred.
• Experience working with financial, investment, asset management, private equity, or research-focused data environments.
• Background building analytics, reporting, and investment data solutions at scale.
• Passion for solving complex business and investment challenges through technology and data.