Senior Data Engineer

Join Hamilton Lane, a global leader in private markets, as we scale to meet the demands of our growing client base. Here, you’ll work with ambitious, high‑performing teams built on integrity, candor and collaboration, backed by our market-leading data and technology. We invest heavily in our people and our partners, giving you the platform to enrich lives, safeguard futures and grow your career.     What We Do  As one of the largest private markets investment firms globally, we provide innovative solutions to institutional and private wealth investors around the world, specializing in flexibility and full-spectrum access. We currently employ approximately 800 professionals operating in offices throughout North America, Europe, Asia Pacific and the Middle East, and have $1.0 trillion in assets under management and supervision, composed of $146.1 billion in discretionary assets and $871.5 billion in non-discretionary assets, as of December 31, 2025.   The Opportunity: We are seeking a talented Senior Data Engineer with strong experience in Python and Snowflake to join our dynamic team. As an Senior Data Engineer, you will play a critical role in our expanding data engineering team. You will be responsible for designing, developing, and maintaining scalable data integration solutions primarily using Python (PySpark), Snowflake, and modern cloud data platform technologies, ensuring the accuracy, reliability, and availability of data for analytics and business decision-making. You will work closely with data architects, data scientists, analysts, and business stakeholders to deliver high-quality, well-structured data products that support advanced analytics, reporting, and operational use cases. If you are passionate about data engineering, enjoy building modern cloud data platforms, and are eager to leverage Snowflake's capabilities to drive business value, we'd love to hear from you. Your responsibilities will be to: Data Engineering & ETL Development Design, develop, and maintain scalable ETL/ELT data pipelines using Python (PySpark), Snowflake, and cloud-native integration technologies. Build reliable, efficient, and reusable data ingestion, transformation, and loading processes to support enterprise analytics and reporting needs. Snowflake Data Platform Utilize Snowflake's architecture and capabilities to design, build, and optimize modern cloud data solutions. Implement and manage Snowflake objects including databases, schemas, tables, views, streams, tasks, stages, and stored procedures. Leverage Snowflake features such as virtual warehouses, data sharing, time travel, and automated scaling to maximize performance and cost efficiency. Data Warehousing Apply expertise in dimensional modeling, star schemas, facts, and dimensions to design and implement scalable enterprise data warehouse solutions within Snowflake. Develop data models that balance business requirements, performance, and maintainability. Data Source…