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Asset Allocator Jobs (NOW HIRING)

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Asset Allocator information

See salary details

$35.5K

$94.1K

$164.5K

How much do asset allocator jobs pay per year?

As of Jul 2, 2026, the average yearly pay for asset allocator in the United States is $94,129.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $109,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Asset Allocator, and why are they important?

To thrive as an Asset Allocator, you need a strong background in finance, investment analysis, and portfolio management, typically supported by a degree in finance or economics and often a CFA designation. Familiarity with asset allocation models, portfolio management software, and risk assessment tools is essential. Outstanding analytical thinking, decision-making, and communication skills help you interpret market trends and articulate strategy to stakeholders. These competencies are crucial for optimizing investment returns while managing risk in dynamic market environments.

What is the difference between Asset Allocator vs Portfolio Analyst?

AspectAsset AllocatorPortfolio Analyst
CredentialsCFAs, finance degreesFinance degrees, certifications like CFA
Work EnvironmentInvestment firms, asset managementFinancial institutions, investment teams
Primary FocusStrategic allocation of assets across classesAnalyzing portfolio performance and risk

Asset Allocators focus on developing and implementing investment strategies by distributing assets across various classes, while Portfolio Analysts evaluate existing portfolios' performance and risk. Both roles require financial expertise and often work within the same industry, but their core responsibilities differ: one is strategic, the other analytical.

What are some common challenges faced by Asset Allocators when managing diversified portfolios?

Asset Allocators often face the challenge of balancing risk and return while adhering to client objectives and market conditions. They must continuously monitor global economic trends, re-balance portfolios to respond to market fluctuations, and manage complex client expectations. Additionally, collaborating with research analysts, portfolio managers, and risk teams is essential to make informed decisions and adapt strategies as needed. Staying current with regulatory changes and financial innovations is also key to ensuring portfolios remain compliant and competitive.

What is an Asset Allocator?

An asset allocator is a financial professional or entity responsible for distributing investments among various asset classes, such as stocks, bonds, real estate, and cash, to optimize returns and manage risk according to a client’s goals and risk tolerance. The process involves analyzing market trends, economic conditions, and individual investment objectives to create a diversified portfolio. Asset allocation is a key component of investment strategy because it helps balance risk and return over time.
More about Asset Allocator jobs
What cities are hiring for Asset Allocator jobs? Cities with the most Asset Allocator job openings:
What states have the most Asset Allocator jobs? States with the most job openings for Asset Allocator jobs include:
Infographic showing various Asset Allocator job openings in the United States as of June 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 92% Physical, 4% Hybrid, and 4% Remote job distribution, with an average salary of $94,129 per year, or $45.3 per hour.

Senior Analyst, Data Engineering & Investment Analytics

Castleton Tower

San Francisco, CA • Remote

$88K - $111K/yr

Full-time

Posted 10 days ago


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 ResponsibilitiesInvestment 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

QualificationsRequired:
  • 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