Senior Consultant, Data Engineering & Analytics [Remote]

The Firm

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.

The Opportunity

We're looking for a technical leader who can design and build data platforms for investment firms. This role emphasizes hands-on engineering while maintaining strategic client engagement. You'll architect data warehouses, build production pipelines, and develop quantitative tools that directly support investment decisions.

What you'll get:

• 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

Qualifications

Required:

• 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

Location & Compensation

Location: Hybrid in the NYC area. Expect to travel roughly one week per month for on-site client work.

Compensation:

• Total expected compensation: $250 to $500K+ (commensurate with experience)

• Firm equity available for high performers