EquiLend Tech Stack

Post-trade and securities finance platform for institutional lending and collateral management

Financial Services New York, NY 201–500 employees Founded 2001 Privately Held

EquiLend operates a post-trade infrastructure layer for securities lending and collateral management, built on a polyglot stack (Python, Scala, Java) running streaming workloads via Kafka, Kinesis, and Flink across AWS, GCP, and Azure. The engineering-forward hiring mix and active projects around platform modernization (monolith decomposition, monitoring automation, architectural roadmap updates) suggest internal infrastructure scaling—paired with pain points around operational risk, compliance, and platform reliability, EquiLend is likely refactoring legacy systems while managing regulatory complexity across three continents.

Tech Stack 53 technologies

Core StackPython PySpark Scala Java Kafka Apache Flink Apache Airflow Apache Spark AWS Snowflake Redshift pandas NumPy scikit-learn Kubernetes Terraform Selenium Playwright JavaScript Postman Spark Streaming AWS Kinesis GCP Azure CI/CD Pub/Sub Spire Cucumber Gherkin REST Assured+23 more

What EquiLend Is Building

◆Challenges

Improving project tracking
Managing legal risk
Enhancing market access
Reducing operational risk
Strengthening compliance
Improving platform reliability
Decomposing monolithic systems
Cost-conscious architecture
Improving hr processes and administrative efficiency
Increasing transparency

▲Active Projects

Improving sales contracting processes
Streamlining global payroll landscape
Release planning and execution
Building integrated hr technology stack
Monitoring automation initiative
Post-deployment monitoring improvement
Datalend trade analytics project
Spire platform architectural roadmap
Implementing global onboarding experience
Modernisation programmes

Hiring Activity

Accelerating25 roles · 20 in 30d

Department

Engineering

Support

Legal

Marketing

Ops

Sales

Services

Seniority

Senior

Mid

Junior

Lead

Principal

Notable leadership hires: Country Lead

Company intelligence

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

Get started free

About EquiLend

EquiLend is a financial technology firm serving the securities finance, collateral management, and swaps industries with trading, post-trade processing, market data, and regulatory technology solutions. The company operates across North America, EMEA, and Asia-Pacific, maintaining offices in the United States, United Kingdom, Ireland, India, and Japan. With 201–500 employees and active hiring across engineering, sales, legal, and operations, EquiLend balances product development with regulatory compliance and multi-jurisdictional operations. The platform handles securities lending workflows, collateral optimization, and regulatory reporting (SFTR, ALD) for institutional clients.

HeadquartersNew York, NY

Company Size201–500 employees

Founded2001

Hiring MarketsUnited States, India, Japan, United Kingdom

Frequently Asked Questions

What tech stack does EquiLend use?

Python, Scala, Java, Kafka, Spark Streaming, Apache Flink, Snowflake, Redshift, AWS, GCP, Azure, Kubernetes, and Terraform. Testing tools include Selenium, Playwright, Cucumber, and REST Assured.

Where does EquiLend hire engineers?

EquiLend has 5 active engineering roles and hires across the United States, India, United Kingdom, and Japan. Hiring velocity is accelerating.

What is EquiLend working on?

Active projects include platform architectural roadmap updates, monolithic system decomposition, post-deployment monitoring improvements, datalend trade analytics, global payroll and HR technology modernization, and sales contracting process automation.

How this profile is built

EquiLend's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.