Senior Consultant, AI & Data Engineering

Castleton, Town of Inc
New York, NY, United States
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$250,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Airflow Amazon Web Services Microsoft Azure Cloud Computing Data as a Services Information Engineering Data Governance Data Transformation Data Warehousing Python (Programming Language) NumPy
+11 more
Query Optimization Web Applications Cloud Platform System Snowflake Apache Spark Pandas Data Lakes Scikit Learn Data Management Data Pipelines Databricks

Job description

  • Strategic Impact: Lead full-scope projects from architecture design to production deployment
  • Direct Mentorship: Work alongside the firm’s Principals on every engagement
  • Modern Tech Stack: Work with best-in-class tools (Snowflake, Databricks, dbt, Dagster, cloud infrastructure, etc.) and cutting-edge AI/agentic development workflows
  • Path to Partnership: Clear trajectory toward firm equity and partnership for high performers

Core Responsibilities

Technical Leadership

  • 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

Client Engagement

  • 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

Requirements

  • 7+ years of hands-on experience in a technical or analytical role (Quant, Quant Dev, Data Scientist, or Data Engineer). Minimum of 5 years for highly exceptional candidates
  • Prior experience at hedge funds, fintech firms/startups, market makers, or top-tier asset management firms. Experience at top technology or strategy consulting firms considered on a case-by-case basis
  • Demonstrated project leadership, ideally overseeing technical delivery from inception to production
  • Proficiency in Python (Pandas, NumPy, Scikit-learn) and advanced SQL query optimization
  • Experience with at least one major cloud platform (AWS, GCP, or Azure) and associated data services (Snowflake, Databricks)
  • Deep understanding of data modeling and data warehousing principles

Valued:

  • Familiarity with data pipeline orchestration tools (Airflow, Dagster, Prefect)
  • Experience building quantitative trading or investment tools
  • Background in financial data (market data, portfolio analytics, fund accounting)

Personal Attributes:

  • High ownership mentality: you see problems through to resolution without being told
  • Understands what high-quality work looks like and how to deliver it
  • Curious and interested in learning about new technologies and the investment industry
  • Seeks to understand the broader business context, not just the technical requirements
  • Independent thinker who takes initiative

Benefits & conditions

  • Total expected compensation: $250 to $500K+ (commensurate with experience)
  • Firm equity available for high performers

About the company

Castleton Tower is a boutique consulting firm founded by executives who have built and led quantitative research, data science, and technology teams at top-tier hedge funds and asset managers. We work exclusively with investment management firms (RIAs, family offices, hedge funds, and asset allocators) helping them modernize their data infrastructure and build AI-ready foundations.

What makes us different: We’re a lean firm where senior practitioners do the actual work. No armies of junior consultants learning on your dime. Our engagements blend high-level strategy with hands-on technical implementation. We’ll assess your technical & business strategy, design your data architecture and also code up the full stack infrastructure where needed.

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