DQE, Data Quality Everywhere Tech Stack

Data quality and deduplication platform for customer contact and identity data

Software Development Miami – Paris – London – Shanghai 51–200 employees Founded 2008 Privately Held

DQE One processes 10+ billion queries annually across 800+ clients, handling tens of millions of contacts with 150ms average response time. The tech stack is a mix of compiled languages (C/C++) and Python, with heavy reliance on PostgreSQL, Redis, and LMDB for performance-critical workloads—and the project list shows an active migration from C/C++ to Python, alongside CI/CD pipeline implementation. This signals a modernization effort to balance legacy performance with maintainability as the company scales contact processing.

Tech Stack 36 technologies

Core StackPython GitLab Linux Salesforce Apex JavaScript HubSpot C++ FastAPI Redis PostgreSQL GitLab CI/CD Magento Jira Zendesk Ansible C/C++ Git Windows REST SOAP Lemlist LinkedIn Sales Navigator Cognism Sanic CherryPy LMDB SQLite Swagger Bash+6 more

What DQE, Data Quality Everywhere Is Building

◆Challenges

Improving internal processes
Maintaining legacy products
Migrating legacy c/c++ products to python
Real-time data cleaning
Efficient data deduplication
Expanding into usa market
Scaling sales pipeline
Ensuring data quality for large salesforce customers
Modernizing legacy architecture
Optimizing performance on large data volumes

▲Active Projects

Implementing ci/cd pipeline
Maintaining core applications
Migrating c/c++ products to python
Salesforce connector evolution
Standalone platform development
Improving outbound sequences
Enhancing email templates
Optimizing call scripts
Modernizing software base to modular architecture
Developing high-performance data processing engines

Hiring Activity

Decelerating8 roles · 2 in 30d

Department

Engineering

Ops

Sales

Seniority

Senior

Junior

Mid

Manager

Company intelligence

Find more companies like DQE, Data Quality Everywhere by tech stack, pain points and active projects

Get started free

About DQE, Data Quality Everywhere

DQE Software, founded in 2008, builds DQE One, a modular data quality management platform specialized in customer contact and identity data validation. The product suite includes DataQ (contact quality), Unify (deduplication), and Enrich (data enrichment), with native connectors to Salesforce, Microsoft Dynamics, Adobe Commerce, Shopify, and Magento. The platform processes customer data across postal addresses, email, phone, and legal fields, interfacing with 240+ international address databases. DQE operates from Miami, Paris, London, and Shanghai, serving over 800 clients across multiple industries and business functions (CRM, CDO, CIO teams). The engineering organization is focused on modernizing a legacy C/C++ codebase to Python while maintaining performance on large-scale contact datasets.

HeadquartersMiami – Paris – London – Shanghai

Company Size51–200 employees

Founded2008

Hiring MarketsFrance

Frequently Asked Questions

What tech stack does DQE use?

C/C++, Python, PostgreSQL, Redis, LMDB, GitLab CI/CD, Salesforce/Apex, and FastAPI. The company is actively migrating legacy C/C++ products to Python while maintaining high-performance data processing engines.

Where is DQE Software headquartered?

DQE operates from four locations: Miami, Paris, London, and Shanghai. Founded in France in 2008, the company maintains offices across Europe, North America, and Asia.

How many clients does DQE serve?

DQE One is used by more than 800 clients across all industries. The platform processes over 10 billion queries annually with an average response time of 150 milliseconds.