Director – AI & Data Engineering

Castleton Tower Consulting, LLC

Lead AI and data engineering at a consulting firm specializing in modernization for investment management. Drive team design, platform architecture, and stakeholder partnerships.

Posted 5/12/2026full-timeNew York • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AirflowCloudPythonSQL

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

10+ years of progressive experience in data engineering, analytics engineering, data platforms, or technical data leadership.
3+ years managing engineers, analytics engineers, data platform teams, or cross-functional technical delivery teams.
Proven ability to design and build production data platforms using Python, SQL, modern warehouse/lakehouse technologies, and orchestration tools.
Strong architectural judgment across data modeling, governance, quality, observability, security, and operational resilience.
Practical fluency with AI-assisted development tools such as Claude Code, OpenAI Codex, Cursor, GitHub Copilot, or similar systems.
Ability to communicate clearly with senior non-technical stakeholders and translate business needs into durable technical systems.
Executive presence, high ownership, and comfort operating in ambiguous environments.

Benefits

Comp & perks

Competitive total compensation commensurate with experience.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data engineeringanalytics engineeringdata platformsproduction data platformsPythonSQLdata modelinggovernanceobservabilitysecurity

Soft Skills

communicationleadershipownershipexecutive presenceoperating in ambiguous environments