Senior Analyst, Data Engineering & Investment Analytics

Castleton Tower Consulting, LLC; San Francisco (CA); Hybrid; USD 100,000 - 150,000; Full time

Job summary

Castleton Tower Consulting, LLC is seeking a skilled data engineering and investment analytics professional located in the Bay Area. The role blends technical work and client engagement, where you will build data infrastructure and derive insights for investment decisions. You need 5+ years of experience in relevant fields, strong proficiency in Python and SQL, and familiarity with tools like Snowflake and Databricks. The position offers competitive compensation with a path to growth within the firm.

Qualifications

• 5+ years of hands-on experience in data/analytics engineering.
• Prior experience in investment management or related financial services.
• Proficiency in Python and SQL for analytical work.

Responsibilities

• Partner with investment professionals to understand their analytical needs.
• Build customized dashboards and quantitative investment applications.
• Design and implement scalable data platforms for investment firms.

Skills

Data/analytics engineering

Business analysis

Investment analytics

Python

Advanced SQL

Data modeling

Tools

Snowflake

Databricks

Airflow

Tableau

Job description

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 (asset allocators, asset managers, hedge funds, family offices, and RIAs) 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 code up the full‑stack infrastructure where needed.

The Opportunity

We’re looking for someone who lives at the intersection of data engineering and investment analytics. You’ll be equally comfortable building a production data pipeline in Python and presenting portfolio analytics insights to a CIO. This role blends hands‑on technical work with strategic client engagement — you’ll build the data infrastructure and derive the business insights that drive investment decisions.

This is not a pure engineering role or a pure strategy role. It’s both. You’ll design Snowflake schemas in the morning, build dbt models after lunch, and walk a client through their portfolio risk dashboard before the end of day.

What you’ll get

• Strategic Impact: Lead full‑scope projects from architecture design through analytics delivery — not just strategy decks or just code
• Direct Mentorship: Work alongside the firm’s Principals on every engagement
• Modern Tech Stack: Work with best‑in‑class tools (Snowflake, Databricks, dbt, Dagster, Sigma, AWS, etc.) and cutting‑edge AI/agentic development workflows
• Path to Growth: Clear trajectory toward expanded responsibilities, with potential to transition into a senior role at a leading Bay Area asset allocator

Core Responsibilities

Investment Analytics & Client Engagement

• 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

Data Engineering & Technical Delivery

• 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

Bridging the Gap

• 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

Qualifications

Required

• 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

Valued

• 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

Personal Attributes

• High ownership mentality: you see problems through to resolution without being told
• Equally curious about the data engineering and the investment side
• Comfort with ambiguity and ability to structure unstructured problems
• Executive presence to hold your own with senior investment leaders
• Independent thinker who takes initiative and understands what high‑quality work looks like

Location & Compensation

Location

Bay Area (hybrid).

Compensation

• Competitive total compensation commensurate with experience
• This role offers a path to join a leading Bay Area‑based asset allocator, with an anticipated transition by January 2027