Castleton Tower Consulting, LLC

Data Engineer

• Design and implement the data team structure, hiring plan, delivery model, and long-term technical roadmap.
• Set engineering standards for code review, testing, documentation, observability, data quality, and production support.
• Manage internal team members, contractors, vendors, and implementation partners where appropriate.
• Build a culture of ownership, technical rigor, and pragmatic delivery.
• Architect and build scalable data platforms across warehouse, lakehouse, orchestration, transformation, and BI layers.
• Develop data models and applications that support portfolio analytics, investment operations, risk reporting, finance, and executive reporting.
• Create durable pipelines and controls for high-value investment and operational datasets.
• Evaluate and rationalize tooling across Snowflake, Databricks, dbt, Dagster/Airflow, cloud infrastructure, BI, and internal applications.
• Use AI coding assistants and agentic workflows to accelerate software and data delivery while maintaining security, review, and testing discipline.
• Identify high-leverage AI use cases across data ingestion, documentation, analytics, workflow automation, and research operations.
• Design human-in-the-loop processes for AI-generated code, analysis, and operational outputs.
• Help the organization build the data and governance foundation required for responsible AI adoption.

Director – AI & Data Engineering

• Lead the design and implementation of scalable data platforms (data warehouses, data lakes) and end-to-end data pipelines
• Develop and optimize production-grade code (Python/Spark) for data transformation and financial analysis
• Build customized analytical applications, dashboards, and quantitative investment tools
• Ensure efficient delivery and adherence to data governance and integrity standards
• Collaborate with client investment teams to translate investment process requirements into robust, automated tools and data products
• Provide technical and project leadership across engagements
• Understand client business context to ensure technical solutions solve real problems

Senior Consultant, AI & Data Engineering

• Partner with investment professionals (PMs, CIOs, COOs, Heads of Operations) to understand their analytical needs and translate them into data products
• Build customized dashboards, analytics tools, and quantitative investment applications
• Present data-driven insights and recommendations to senior client stakeholders
• Identify opportunities where better data infrastructure can improve investment processes
• Design and implement scalable data platforms (data warehouses, data lakes) and end-to-end data pipelines for investment firms
• Develop and optimize production-grade code (Python/SQL) for data transformation and financial analysis
• Build and maintain data models that support portfolio analytics, risk reporting, and investment operations
• Leverage AI-assisted development tools to accelerate delivery
• Translate business requirements from investment teams into robust technical architectures
• Own projects end-to-end: from scoping the business problem, to building the data layer, to delivering the analytics
• Ensure technical solutions are grounded in real investment workflows, not just technically elegant

Director – AI & Data Engineering

Senior Consultant, AI & Data Engineering

Senior Analyst, Data Engineering – Investment Analytics