Senior Data Engineer — Remote, Equity & Global Impact

Highlights

Location:

Remote (CET hours preferred)

Compensation: GEL
11,900 - GEL
13,800 gross + stock options

Language:
Russian-speaking team, English B1+ required

We’re Fundraise Up - a global fundraising platform built to make donating to nonprofits fast, seamless, and accessible to all. Every month, our technology powers tens of millions of dollars in donations across the globe. We focus on innovation that directly impacts results: faster load times, higher conversion rates, global payment support, and accessibility-first design.

Our platform is trusted by many of the world’s leading nonprofits, including UNICEF, the Alzheimer’s Association, and a wide range of global NGOs. With a 4.9/5 rating across top software review platforms, we’re recognized not just for our impact – but for the quality of the product we deliver.

We operate in the enterprise segment, serving nonprofit organizations across North America, the United Kingdom, Australia, and Europe.

We’re building a large and complex product ecosystem that serves nonprofits, donors, and partners around the world. The platform includes a modern checkout experience and customizable widgets (each a standalone SPA), donor, organization, and partner portals, admin tools, and several internal apps.

Our backend is powered by Node.js (Koa, NestJS) and Mongo

DB. The frontend stack includes Webpack, Vue.js, and React, with nearly all code written in Type Script. For high-throughput messaging and background processing, we use Kafka (for millions of events) and Bull (Redis). Analytics data is stored in Click House, and we use Elasticsearch for search.

We are a distributed team of 160+ product professionals, including 80+ engineers. Our team members are mainly based across Spain, Poland, Portugal, Georgia, Armenia, Serbia, Turkey, and Cyprus. Many of our developers bring 5 - 10+ years of experience, and we foster a culture of deep technical curiosity and knowledge sharing.

Despite our scale, we operate like a focused team – where every task matters and every voice is heard. We value thoughtful collaboration, strong engineering practices, and a product mindset. You’ll be joining a team where quality, mentorship, and mutual respect come first.

As a Senior Data Engineer, you will be responsible for designing, building, and optimizing scalable data pipelines and ETL/ELT processes.

At the initial stage, you will be the first engineer in this direction, taking full ownership of the data domain. As the product and data needs grow, we plan to expand the team, and you will have the opportunity to contribute to its development.

This role requires a high level of autonomy and ownership, combined with close collaboration with analytics, Data Science, and engineering teams.

• Design and evolve the architecture of the data platform and storage systems.
• Build reliable ETL/ELT processes and develop scalable data pipelines for delivering data into a centralized analytical warehouse.
• Maintain and further develop the Data Warehouse.
• Collaborate with engineering and analytics teams on system design and architectural decisions.
• Ensure data governance and maintain high standards of data quality.
• Write and optimize queries for Mongo
  
  DB and Click House.
• Manage and maintain workflows in Airflow.
• At Fundraise Up, AI is a default tool, not an experimental one. We expect every team member to actively use AI in their day-to-day work, identify where AI can change the shape of problems in their function, and grow their fluency as the tools evolve. You should already be using AI meaningfully in your work and understand where it adds value and how it can improve the way you operate.

• Experience: 7+ years of experience as a Data Engineer.
• Programming: 5+ years of experience with Python, Type Script, Node.js, Kafka.
• Strong understanding of data processing algorithms and principles.
• Hands‑on experience with Click House, Airflow, Amazon S3, Git, Docker.
• Solid understanding of Data Lake and Data Warehouse architectures.
• Experience working with large‑scale data and query optimization.
• Ability to work collaboratively toward shared…