echoloc

Guggenheim Investments Tech Stack

Global asset management firm managing fixed income, equity, and alternatives

Financial Services New York, NY 1,001–5,000 employees Privately Held

Guggenheim Investments operates a multi-billion-dollar asset management business across fixed income, equities, and alternatives with 1,001–5,000 employees headquartered in New York. The tech stack reflects a traditional financial services foundation—Bloomberg, Aladdin, DTCC, Workday, Salesforce—paired with engineering tooling (Python, SQL, Go) and security-focused hiring (cloud security initiatives, security awareness programs). Active recruitment across finance, sales, and operations suggests scaling client-facing and operational capacity while addressing persistent pain points in process efficiency and regulatory compliance.

Tech Stack 24 technologies

Core StackWorkday Salesforce Python ADP Go Splunk CrowdStrike PowerPoint Excel Bloomberg Microsoft Office SQL Microsoft 365 Aladdin DTCC Word Microsoft Access Paychex VBA PowerShell Bash Eagle Visio Qualys

What Guggenheim Investments Is Building

Challenges

  • Improving reporting processes
  • Minimizing market risk
  • Increasing assets under management
  • Reducing incidents caused by human error
  • Process inefficiencies
  • Compliance with regulatory requirements
  • Regulatory compliance for complex fixed income products
  • Complex issues beyond tier 1
  • Reducing repeated problems
  • Ensuring documentation accuracy

Active Projects

  • Security awareness program development
  • Cloud security initiatives
  • Create and maintain analytical models and tools that enhance credit research
  • Represent investment capabilities to clients
  • Major module rollouts
  • Integration development between workday and external systems
  • Streamlining pre and post-close processes
  • Enhancing data management
  • Implementing new technologies
  • Process development for cml and land banking loan closings

Hiring Activity

Steady40 roles · 15 in 30d

Department

Finance
11
Sales
8
Ops
6
Operations
3
Support
3
Product
2
Security
2
Compliance
1

Seniority

Senior
13
Mid
11
VP
9
Junior
4
Intern
1
Lead
1
Company intelligence

Find more companies like Guggenheim Investments by tech stack, pain points and active projects

Get started free

About Guggenheim Investments

Guggenheim Investments is a global asset management and investment advisory firm offering fixed income, equity, and alternatives strategies. The organization operates through multiple affiliated investment management entities including partnership investment management, private investments, loan advisory, and wealth solutions divisions, with regional operations in Europe and Japan. The business model combines direct advisory services with fund distribution and private capital strategies. Current operational focus centers on modernizing internal processes—particularly Workday integration, loan closing automation, and analytical tooling—while tightening compliance controls and reducing manual operational errors.

HeadquartersNew York, NY
Company Size1,001–5,000 employees
Hiring MarketsUnited States, India, Canada

Frequently Asked Questions

What is Guggenheim Investments' tech stack?

Core systems include Bloomberg, Aladdin (BlackRock's investment platform), DTCC (post-trade infrastructure), Workday (HR/finance), and Salesforce (CRM). Engineering uses Python, SQL, Go, and VBA. Security stack includes CrowdStrike and Qualys.

Is Guggenheim Investments hiring?

Yes. 41 active roles across finance (11), sales (8), ops (6), support (3), product (2), and security (2). Most recent postings weighted toward senior and VP-level positions. Hiring in US, India, and Canada.

What is Guggenheim Investments working on?

Cloud security initiatives, Workday-to-external systems integration, analytical model development for credit research, loan closing process automation, and enhanced data management. Security awareness and compliance tooling are active focus areas.

Similar Companies in Financial Services

Other companies in the same industry, closest in size