Senior Analyst, Data Engineering & Investment Analytics
About The Position
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. The firm works exclusively with investment management firms (asset allocators, asset managers, hedge funds, family offices, and RIAs) helping them modernize their data infrastructure and build AI-ready foundations. It is a lean firm where senior practitioners do the actual work, blending high-level strategy with hands-on technical implementation, including assessing technical & business strategy, designing data architecture, and coding full-stack infrastructure. The opportunity is for someone who lives at the intersection of data engineering and investment analytics, comfortable building production data pipelines in Python and presenting portfolio analytics insights to a CIO. This role blends hands-on technical work with strategic client engagement, building data infrastructure and deriving business insights that drive investment decisions. It is both an engineering and a strategy role, involving designing Snowflake schemas, building dbt models, and walking clients through portfolio risk dashboards. The role offers strategic impact, direct mentorship from the firm's Principals, work with a modern tech stack (Snowflake, Databricks, dbt, Dagster, Sigma, AWS, etc.) and cutting-edge AI/agentic development workflows, and a clear path to growth with potential to transition into a senior role at a leading Bay Area asset allocator.
Requirements
- 5+ years of hands-on experience in a role that combined data/analytics engineering with business analysis or investment analytics
- Prior experience within investment management, financial services, or firms that serve them (hedge funds, asset managers, fintech, financial consulting)
- Proficiency in Python and advanced SQL for both data engineering and analytical work
- Experience with modern data platforms (Snowflake, Databricks, or similar) and data modeling principles
- Demonstrated ability to communicate technical concepts to non-technical investment professionals
- Comfort working directly with senior clients and managing stakeholder expectations
Nice To Haves
- Experience with data pipeline orchestration tools (Airflow, Dagster, Prefect)
- Background in portfolio analytics, fund accounting, or investment operations workflows
- Familiarity with BI/visualization tools (Sigma, Tableau, Looker)
- Management consulting experience (strategy or implementation)
- Experience building quantitative trading or investment tools
Responsibilities
- 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
Benefits
- Competitive total compensation commensurate with experience
- Path to join a leading Bay Area-based asset allocator, with an anticipated transition by January 2027
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
