Jobs at MerQube

Manage and develop client relationships across onboarding, contracting, launches, reporting, and ongoing account needs. Coordinate with Sales, Legal, Product, Finance, and Index Production to resolve issues and keep projects moving. Maintain accurate client and pipeline data in Salesforce, support sales operations, track milestones, and improve client service processes and reporting. The role offers progression toward independent account ownership in a financial technology environment.

Supports client relationships across onboarding, contracting, launches, reporting, and ongoing account management. Coordinates with Sales, Legal, Product, Finance, and Index Production to resolve client needs, track milestones, maintain Salesforce records, monitor pipeline activity, and improve reporting and processes. The role develops toward independent ownership of assigned client accounts within a financial technology and index-provider environment.

Design, build, and operate scalable AWS data pipelines and lakehouse platforms for market data and index computation. Modernize legacy ETL systems, curate financial datasets, develop canonical data models, and implement data quality, governance, lineage, and observability frameworks. Collaborate with product, research, index operations, and engineering teams while monitoring production systems and supporting on-call operations.

Owns and operates AWS cloud infrastructure and data platforms supporting index computation and analytics. Responsibilities include managing Airflow, Kafka, ETL pipelines, databases, CI/CD, Docker, Kubernetes, Helm, and EKS; improving monitoring, reliability, security, IAM, secrets management, and compliance; leading incident response; and mentoring engineers.

As a Quantitative Associate, you will develop and backtest index strategies using Python, analyze financial data, and collaborate with teams to enhance financial solutions.

Join MerQube's New York team to model, backtest, and launch indices and options-based strategies. Develop implied volatility and pricing frameworks for options and exotic derivatives, translate models into production-ready Python indices, collaborate with financial engineering and clients, use datasets like FactSet and LSEG Refinitiv, and contribute to thought leadership.