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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Fundraise Up - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon S3, Apache HTTP Server, Big Data, Computer Programming, Data Governance, Extract Transform Load (ETL), Data Warehousing, Python (Programming Language), MongoDB, Node.Js, Query Optimization, TypeScript, Parquet, Data Processing, Git, Data Lakes, Apache Kafka, Machine Learning Operations, Vertica, Data Pipelines, Docker - **Published:** June 24, 2026 - **Apply:** https://www.dice.com/job-detail/d34c455f-dff6-4138-b46f-c95eca04ea7f ## About the Role * Experience: 7+ years of experience as a Data Engineer. * Programming: 5+ years of experience with Python, TypeScript, Node.js, Kafka. * Strong understanding of data processing algorithms and principles. * Hands-on experience with ClickHouse, 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 goals. * Strong sense of ownership, responsibility, and proactivity. * English level: B1+. Nice to Have * Experience with Apache Parquet, MLflow, MongoDB. ## Description 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. What You'll Do * Develop a 1-2 year roadmap for the Data Warehouse platform. Evaluate the efficiency of the current tech stack. * Build reliable ETL/ELT processes and develop scalable data pipelines for delivering data into a centralized analytical 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 MongoDB and ClickHouse. * 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., * Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace * English learning courses * Relevant professional education * Gym or swimming pool * Co-working * Remote working **Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company. We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other characteristic protected by applicable law in the countries where we operate. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)