
51 - 200 employees
🤲 Charity
💳 Fintech
☁️ SaaS
Charity • Fintech • SaaS
Fundraise Up is a digital platform that revolutionizes the way nonprofits conduct online fundraising. It offers a suite of tools designed to enhance donor engagement and boost conversion rates, including optimized campaign pages, a checkout system, and pre-built UI components. Fundraise Up supports global fundraising with multi-language capabilities and provides comprehensive security features to protect both donor data and the fundraising process. It integrates seamlessly with various platforms and uses artificial intelligence to personalize the donation experience. Its mission is to maximize donations for causes worldwide through innovative technology and strategic partnerships with nonprofits.
🕒 April 23
🗣️🇷🇺 Russian Required
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51 - 200 employees
🤲 Charity
💳 Fintech
☁️ SaaS
Charity • Fintech • SaaS
Fundraise Up is a digital platform that revolutionizes the way nonprofits conduct online fundraising. It offers a suite of tools designed to enhance donor engagement and boost conversion rates, including optimized campaign pages, a checkout system, and pre-built UI components. Fundraise Up supports global fundraising with multi-language capabilities and provides comprehensive security features to protect both donor data and the fundraising process. It integrates seamlessly with various platforms and uses artificial intelligence to personalize the donation experience. Its mission is to maximize donations for causes worldwide through innovative technology and strategic partnerships with nonprofits.
• 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 MongoDB and ClickHouse. • Manage and maintain workflows in Airflow.
• 7+ years of experience as a Data Engineer. • 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+.
• Private medical insurance for the employee and their family • 23 paid vacation days per year • 11 paid public holidays per year • 5 company-paid sick leave days • English learning courses. • Relevant professional education • Gym or swimming pool • Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace • Co-working • Remote working
Apply Now🕒 April 16
501 - 1000
Middle Data Engineer specialized in Azure Databricks developing data pipelines for a global IT services company. Collaborate with teams on cloud-based data architectures using modern technologies.
Azure
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ETL
PySpark
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🕒 April 16
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Middle Data Engineer specializing in Azure Databricks at Miratech, designing modern data pipelines and Lakehouse architectures.
Azure
Cloud
ETL
PySpark
Spark
SQL
SSIS
🕒 April 16
501 - 1000
Middle Data Engineer specialized in Azure Databricks for Miratech. Focused on designing and developing modern data pipelines and Lakehouse architectures.
Azure
Cloud
ETL
PySpark
Spark
SQL
SSIS
🕒 April 16
501 - 1000
Middle Data Engineer specializing in Azure Databricks to design and develop modern data pipelines. Join Miratech to support digital transformation across global enterprises.
Azure
Cloud
ETL
PySpark
Spark
SQL
SSIS
🕒 April 16
501 - 1000
Join Miratech as a Middle Data Engineer specializing in Azure Databricks. Design and develop modern data pipelines and Lakehouse architectures in a collaborative environment.
Azure
Cloud
ETL
PySpark
Spark
SQL
SSIS