Vice President, Data Engineer

Altriarch is a leading private credit asset management firm specializing in asset-based lending (ABL). Founded in 2021 in Charleston, SC, the firm manages capital on behalf of institutional and private investors nationwide. Altriarch delivers flexible credit solutions to middle-market companies, structuring loans secured by receivables, inventory, equipment, and other assets to unlock working capital and fuel growth.

Altriarch is seeking a highly capable Data Engineer to design and build the data infrastructure that powers the Firm’s investment, operations, and reporting capabilities. This is a foundational role at a firm that is actively modernizing its data architecture, replacing fragmented automations with production-grade pipelines and establishing a single, reliable source of truth across all source systems. Reporting directly to the Firm’s Chief Data Officer, the Data Engineer will own the end-to-end data stack, including ingestion, transformation, modeling, data quality, and access governance.

The role requires deep technical expertise paired with the ability to navigate a complex, multi-system financial data environment.

Looking ahead, this role is central to Altriarch’s AI roadmap. Once the Snowflake warehouse is live, the Data Engineer will serve as the primary technical conduit between Claude (Altriarch’s AI platform), internal employee use cases, and the data warehouse, enabling a new generation of advanced workflows. This is not a background infrastructure role; it is a front-row seat to how AI and clean data transform a private credit firm.

The Data Engineer will be a fully integrated member of Altriarch’s internal technology team, a cross-functional group that includes AI consultants, IT teams (outsourced MSP), Operations, and other data warehouse initiative resources. The team operates on a weekly cadence, and this role is expected to participate actively, maintaining visibility into active Claude projects, IT infrastructure and compliance decisions, and operational workflows so that the data layer is built in sync with the systems it must serve.

• Evaluate and recommend the optimal data architecture (data lake, data warehouse, or hybrid) for Altriarch’s systems and data volumes; produce a written recommendation.
• Build and maintain the central Snowflake data warehouse, including virtual warehouses, stages, streams, tasks, RBAC configuration, and native lineage/Access History.
• Design scalable, production-grade ingestion pipelines from Tenor, Factor View, Affinity, Asana, and Investran (FIS Investment Data Platform) into Snowflake.
• Serve as the technical bridge between the Snowflake warehouse and Claude-powered workflows, ensuring data is structured, permissioned, and searchable by AI agents.
• Architect the warehouse with AI use cases and business requirements; schema design, access patterns, and governance must support Claude agent queries from day one, not be retrofitted later.

• Design and implement a canonical data model using star/snowflake schemas covering loans, borrowers, positions, transactions, and investors across source systems with known schema mismatches and duplications.
• Author complex SQL queries, window functions, and CTEs against financial datasets; optimize for performance at scale.
• Replace existing Zapier automations with scheduled, production-grade ETL/ELT pipelines using Python and Snowflake-native tasks.

• Build REST API connectors to Factor View, Affinity, and Asana, handling authentication, pagination, rate limiting, and error recovery.
• Write Python-based transformation logic, automate ingestion pipelines, and manage file-based exports from systems without native API support.
• Leverage AWS (S3 for raw storage; Lambda or Glue for orchestration) as the preferred cloud host per vendor recommendation;
  Azure/GCP alternatives considered.

• Implement automated validation frameworks, deduplication logic, and exception reporting to establish and maintain data hygiene standards across all source systems.
• Configure role-based access control…