Overview • Collaborate with a dynamic data team to design, build, and optimize data pipelines and infrastructure supporting financial analytics. • Work primarily with Snowflake, dbt, Dagster, and AWS to manage data ingestion and storage processes. • Support a team of Analytics Engineers by ensuring accurate and reliable data for lending decisions. • Engage with external counterparties to address data-related matters and maintain quality standards. • Contribute to AI agent operations, supporting deployment and maintenance of AI-driven data workflows. • Participate in a fast-paced environment, adapting to evolving business requirements and emerging tools. • Ensure data governance principles are upheld in all data modeling and transformation tasks. • Document data processes comprehensively to support team knowledge-sharing and auditability. Key Responsibilities & Duties • Design and optimize batch data pipelines and ELT processes for efficient data ingestion and retrieval. • Develop and extend dbt projects, focusing on schema design and pipeline reliability. • Maintain Dagster orchestration for batch ingestion pipelines, ensuring reliable scheduling and observability. • Build and manage Snowflake-AWS integrations, including S3 storage and IAM roles. • Support data quality workflows, identifying inconsistencies and implementing resolutions. • Define and maintain data models and schemas for efficient analytics and reporting. • Document data structures and pipeline flows for team collaboration and audit purposes. • Collaborate with stakeholders to translate business requirements into reliable data infrastructure. Job Requirements • Bachelor's degree in Data Science, Information Systems, Computer Science, or related field. • Minimum of 2 years of experience in Data Engineering or Analytics Engineering roles. • Proficiency in SQL and Python for data pipeline development, including Pandas. • Hands-on experience with Snowflake, dbt, Dagster, and AWS services. • Solid understanding of data modeling, ETL/ELT design patterns, and governance principles. • Experience with finance-related data and REST API integration preferred. • Familiarity with AI/ML tooling or LLM-based pipeline development is a plus. • Effective communication skills with technical and non-technical stakeholders.