Role Overview
We are seeking a hands-on Senior / Lead Data Engineer to provide technical leadership for the platforms, pipelines, and data products that power analytics, applications, and investment decision-making across the firm. You will architect scalable, cloud-first data solutions; set engineering standards; and lead small teams through delivery of reliable, analytics-ready datasets and services.
This role combines deep technical execution with mentorship, cross-functional partnership, and ownership of complex data initiatives. It offers the opportunity to take on people-management responsibilities over time.
What You’ll Do
• Lead the design and delivery of scalable ingestion pipelines, data models, and platform services using Python, SQL, Snowflake, and AWS.
• Architect reliable solutions for structured, unstructured, market, and alternative datasets, with particular focus on performance, lineage, usability, and operational resilience.
• Drive the evolution of the Data Acquisition Platform, including APIs, services, plugins, and 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 and growing dataset estate.
• Lead root-cause analysis for complex, time-sensitive data incidents and drive durable corrective actions.
• Mentor engineers through design reviews, code reviews, pairing, and technical coaching; help shape team practices and engineering culture.
• Partner directly with Analysts, Quants, Portfolio Managers, and external data providers to translate requirements into robust end-to-end data solutions.
• Evangelize data engineering best practices and influence technical direction across partner teams.
• Potentially manage a small team, including prioritization, delivery planning, feedback, and career development.
What You’ll Bring
• Significant experience building and operating production data platforms, pipelines, and analytics-ready data products.
• Strong Python and SQL skills, with experience across relational and NoSQL data systems.
• Deep experience with Snowflake or comparable modern cloud data warehouses.
• Strong hands-on experience with AWS data and cloud services, including designing secure, scalable, and cost-effective production architectures.
• Experience designing and orchestrating production workflows with Airflow or comparable tools.
• Cloud infrastructure experience in AWS, Azure, or Google Cloud.
• Strong understanding of data modeling, large-scale dataset performance, time-series data, and temporal-query patterns.
• Demonstrated ability to lead technical projects end-to-end, make sound architectural decisions, and improve existing complex systems.
• A track record of mentoring engineers and communicating effectively with both technical and business stakeholders.
Nice to Have
• Experience with Go and service-oriented platform development.
• Experience applying AI/LLM capabilities to data engineering workflows.
• Financial-services or market-data experience.