Senior Consultant, AI & Data Engineering
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Role details
Tech stack
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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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