Data Engineer

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.