Associate, Data Engineer

Basepoint Capital, LLC • New York, NY

3d • Onsite

About The Position

As a Data Engineer at BasePoint, you will own and evolve our batch data ingestion layer, supporting a team of 10 Analytics Engineers who build collateral analytics for private credit facilities. Our data arrives from borrowers and sellers on fixed schedules, and the accuracy of that data directly determines our lending decisions. You will work primarily in Snowflake, dbt, Dagster, and AWS, and you will be embedded in a 16-person data team that serves Credit, Operations, and Finance as its primary stakeholders.

You will collaborate with Analytics Engineers, Business Intelligence Engineers, and the Director of Data Platforms to translate business requirements into reliable, well-documented data infrastructure. You will also engage directly with external counterparties on data-related matters when needed.

Requirements

• Bachelor's degree in Data Science/Analytics, Information Systems, Computer Science, or a related field.
• 2+ years of experience in a Data Engineering or Analytics Engineering role. Candidates with a strong analytics background and demonstrated pipeline development experience will also be considered.
• Experience working with finance-related data (FinTech, lending, financial services, or related industries preferred).
• Advanced SQL skills and demonstrated experience working with complex, multi-source data sets.
• Proficiency in Python for data pipeline development. Pandas required; Polars or PySpark a plus.
• Hands-on experience with core data engineering tools, including: Snowflake (data warehousing), dbt (data transformation and modeling), Dagster or Airflow (pipeline orchestration), AWS (S3, IAM, CloudFormation, or related services), REST API integration (data ingestion, outbound data delivery, and API-driven orchestration).
• Solid understanding of data modeling, ETL/ELT design patterns, and data governance principles.
• Strong attention to detail and a commitment to accuracy. In our environment, data quality has direct financial implications.
• Effective communication skills with both technical and non-technical stakeholders, including Credit and Operations teams who rely directly on the data this role supports.
• Willingness to stay current with emerging tools and practices, and ability to adapt to evolving business requirements in a fast-paced environment.

Nice To Haves

• Familiarity with AI/ML tooling or LLM-based pipeline development is a plus, including any of the following: Snowflake Cortex (AI functions, Cortex Analyst, or Snowflake Intelligence), AWS Bedrock (LLM model access and deployment via AWS infrastructure), Anthropic Claude API (prompt engineering, API integration, or embedding LLM calls into data workflows)

Responsibilities

• Design, build, and optimize batch data pipelines, ELT processes, and Snowflake data warehouse objects to support efficient data ingestion, storage, and retrieval.
• Contribute to and extend the firm's dbt project, including seed management, model graph optimization, schema design, and pipeline reliability.
• Maintain and expand Dagster orchestration for batch ingestion pipelines, ensuring reliable scheduling and observability across daily, weekly, and monthly data loads.
• Build and maintain Snowflake-AWS integrations including S3 storage integrations, IAM roles, and CloudFormation configurations supporting our cloud data layer.
• Support data quality and reconciliation workflows for collateral data pledged against lending facilities. Identify inconsistencies and anomalies and implement appropriate resolutions.
• Define and maintain data models and schemas that enable efficient analytics, reporting, and visualization, consistent with data governance standards.
• Document data processes, pipeline flows, and data structures in a way that supports team knowledge-sharing and auditability.
• Support the deployment, monitoring, and ongoing maintenance of AI agents developed by the data team, including managing data sources, pipeline dependencies, and integrations that those agents rely on.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level