Lead Data Engineer

As a hands-on Senior/Lead Data Engineer, you’ll architect scalable, cloud-first data solutions and guide data platforms supporting analytics and investment decisions. You’ll lead design and delivery of pipelines, data models, and platform services, while mentoring engineers and partnering with analysts and portfolio teams. The role blends technical execution with people leadership and ownership of complex data initiatives, with potential people management responsibilities over time. You will shape data engineering standards, drive data quality, and advance end-to-end data solutions that enable actionable insights.

• Design and deliver scalable ingestion pipelines, data models, and platform services using Python, SQL, Snowflake, and AWS
• Architect reliable data solutions for structured, unstructured, market, and alternative datasets with emphasis on performance, lineage, usability, and resilience
• Evolve the Data Acquisition Platform (APIs, services, plugins, AI-enabled workflows) for onboarding, pipeline creation, metadata generation, and natural-language data access
• Establish and improve automated data-quality frameworks covering completeness, freshness, schema integrity, reconciliations, and business-rule validation
• Own technical standards for testing, observability, alerting, incident response, and production support across a large data estate
• Lead root-cause analysis for time-sensitive data incidents and drive durable fixes
• Mentor engineers through design reviews, code reviews, pairing, and coaching; shape team practices and engineering culture
• Collaborate with Analysts, Quants, Portfolio Managers, and data providers to translate requirements into end-to-end data solutions
• Advocate data engineering best practices and influence direction across partner teams
• Possibly manage a small team including prioritization, delivery planning, feedback, and career development

• Significant experience building and operating production data platforms and data products
• Strong Python and SQL skills with experience across relational and NoSQL systems
• Deep experience with Snowflake or comparable cloud data warehouses
• Hands-on AWS data and cloud services experience, including scalable, secure architectures
• Experience designing and orchestrating production workflows with Airflow or similar tools
• Cloud exposure in AWS, Azure, or Google Cloud
• Solid understanding of data modeling, large-scale dataset performance, time-series data, and temporal queries
• Proven ability to lead technical projects end-to-end and drive architectural decisions
• Track record mentoring engineers and communicating with both technical and business stakeholders

• Mentoring and coaching
• Cross-functional collaboration
• Strong communication with technical and business stakeholders
• Python
• SQL
• Snowflake