Senior Engineer

Data EngineerWe are looking for a creative and enthusiastic Data Engineer to join our team. In this role, you will help build and maintain scalable data platforms and pipelines that power analytics, applications, and decision-making across the organization. You will work with a wide range of structured and unstructured datasets, design reliable data models, and develop services that make data accessible and useful to end users. The ideal candidate has experience building and supporting modern data infrastructure, working with large-scale datasets, and creating high-quality, analytics-ready data products. This role requires strong technical skills, attention to detail, and the ability to collaborate closely with both technical and business stakeholders.In this role, you will:Develop cloud-first data ingestion processes using Python, SQL, and SparkEngineer data models and infrastructure for a wide variety of market and alternative datasetsDesign and build services and plugins to enhance our Data Acquisition PlatformMaintain alerting systems to ensure smooth day-to-day operations for hundreds of datasetsAuthor tests to validate data quality and the stability of the platformBuild and support AI-enabled workflows that accelerate dataset onboarding, pipeline creation, metadata generation, and natural-language access to dataDesign and evolve rules-based data quality frameworks that automatically validate completeness, freshness, schema integrity, and business logic across datasetsInvestigate and defuse time-sensitive data incidentsCommunicate with data providers to onboard new datasets and troubleshoot technical issuesEvangelize best practices to partners throughout the firmWork directly with Analysts, Quants, and Portfolio Managers to understand requirements and provide end-to-end data solutionsWhat you'll bring:Bachelor's or Master's degree in Computer Science or a related fieldStrong analytical, data, and programming skills (Python, SQL, NoSQL)Strong experience with Snowflake and building analytics-ready datasets in a modern cloud data warehouse3+ years of experience with at least one of Spark, Hive, or Hadoop2+ years of experience orchestrating pipelines with technologies such as Airflow, Luigi, Oozie, or NiFi1+ years of experience with cloud technologies (AWS, Azure, or Google Cloud)Solid understanding of time series data and temporal queriesExperience with large datasets and techniques to architect them for performanceAbility to understand and contribute to existing data systems softwareStrong oral and written communication skills; must be a team playerNice to have:Experience with GoAptitude for designing infrastructure, data products, and tools for Data ScientistsFinancial industry experience