Senior Data Engineer (Azure)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Senior Data Engineer (Azure): Designing and maintaining scalable data processing infrastructure and ETL/ELT pipelines on Azure Databricks with an accent on data lakehouse architecture and performance optimization. Focus on delivering reliable data for AI/ML applications and analytics to support global spend management solutions.
Location: Must be based in or able to work from Cracow, Poland (Hybrid)
Salary: 18,000–25,000 PLN/month gross (Employment) or 20,000–27,000 PLN/month net (B2B)
Company
is a global leader in cloud-based spend management solutions, leveraging AI to simplify accounts payable and financial processes for thousands of organizations worldwide.
What you will do
- Design, develop, and maintain scalable data processing infrastructure and ETL/ELT pipelines on Azure.
- Build and optimize data solutions within Azure Databricks and Data Lakehouse environments.
- Deliver high-quality, reliable data to support AI/ML applications, analytics, and reporting.
- Ensure data governance, security, integrity, and availability across the platform.
- Monitor, troubleshoot, and improve data workflows and platform performance.
- Collaborate with cross-functional teams to implement effective data solutions.
Requirements
- Must be based in or able to work from Cracow, Poland
- Proficiency in Python, including Pandas and PySpark.
- Strong SQL skills and experience with large-scale datasets.
- Hands-on experience with ETL/ELT processes in Data Lakehouse environments.
- Practical experience with Azure cloud services, Apache Spark, and Azure Databricks.
- Understanding of data modeling and modern data engineering best practices.
Nice to have
- Experience with data mesh architecture initiatives.
- Exposure to AI/ML data pipelines.
- Knowledge of data governance, security, and compliance frameworks.
Culture & Benefits
- Work on cutting-edge data and AI technologies.
- Collaborative and meritocratic work culture with supportive leadership.
- Continuous learning and professional development opportunities.
- People-first culture focused on innovation and work-life balance.
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