Senior AI Data Engineer – Financial Data Infrastructure
⚲ Warszawa
23 100 - 33 600 PLN netto (B2B)
Wymagania
- ETL/ELT processes
- SQL
- Apache Spark
- Cloud Platforms (AWS/GCP/Azure)
- Data Pipeline Development
- Apache Kafka
- NoSQL Databases
- Machine Learning Workflows
- real-time data processing
- Financial Industry Knowledge
Opis stanowiska
Unleash the power of data to revolutionize finance — design the future of AI-driven financial infrastructures!
Poland-based opportunity with hybrid work model.
As a Senior AI Data Engineer – Financial Data Infrastructure, you will be working for our client, a leading organization in the finance and banking industry. You will play a pivotal role in building reliable, scalable, and secure data systems that underpin next-generation AI applications in financial services. Your expertise will enable innovative solutions and empower data-driven insights that transform the industry.
Your main responsibilities:
• Design and implement scalable data pipelines and ETL/ELT processes
• Build and maintain data warehouses and data lakes for large-scale financial datasets
• Ensure data quality, consistency, and compliance with industry regulations
• Transform and prepare data for machine learning models and predictive analytics
• Collaborate with AI Engineers and Data Scientists to optimize training and inference pipelines
• Work with real-time data streaming platforms such as Kafka or Spark Streaming
• Manage databases (SQL and NoSQL) ensuring high availability and performance
• Monitor, troubleshoot, and optimize data flows and infrastructure performance
• Contribute to cloud-based data architecture and infrastructure management
• Document data workflows, processes, and best practices
You're ideal for this role if you have:
• Minimum 3 years of experience as a Data Engineer, AI Data Engineer, or similar role
• Proficiency in ETL/ELT processes and data pipeline development
• Strong knowledge of big data technologies such as Spark, Kafka, or Hadoop
• Experience with SQL and NoSQL databases
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) for data engineering solutions
• Understanding of machine learning workflows and data preparation for AI models
• Ability to work with both batch and real-time data processing
• Strong problem-solving skills and attention to detail
• Experience in the finance or banking industry is a strong advantage
• Fluent command of English and Polish, with excellent communication skills
Eligibility to work on this role:
Only candidates with an existing legal right to work in the European Union will be considered for this role.
#MAKEYourCareerBETTER
Interested? Apply now and include your CV in English or Polish, along with a statement confirming your consent to the processing and storage of your personal data.
Poland-based opportunity with hybrid work model.
As a Senior AI Data Engineer – Financial Data Infrastructure, you will be working for our client, a leading organization in the finance and banking industry. You will play a pivotal role in building reliable, scalable, and secure data systems that underpin next-generation AI applications in financial services. Your expertise will enable innovative solutions and empower data-driven insights that transform the industry.
Your main responsibilities:
• Design and implement scalable data pipelines and ETL/ELT processes
• Build and maintain data warehouses and data lakes for large-scale financial datasets
• Ensure data quality, consistency, and compliance with industry regulations
• Transform and prepare data for machine learning models and predictive analytics
• Collaborate with AI Engineers and Data Scientists to optimize training and inference pipelines
• Work with real-time data streaming platforms such as Kafka or Spark Streaming
• Manage databases (SQL and NoSQL) ensuring high availability and performance
• Monitor, troubleshoot, and optimize data flows and infrastructure performance
• Contribute to cloud-based data architecture and infrastructure management
• Document data workflows, processes, and best practices
You're ideal for this role if you have:
• Minimum 3 years of experience as a Data Engineer, AI Data Engineer, or similar role
• Proficiency in ETL/ELT processes and data pipeline development
• Strong knowledge of big data technologies such as Spark, Kafka, or Hadoop
• Experience with SQL and NoSQL databases
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) for data engineering solutions
• Understanding of machine learning workflows and data preparation for AI models
• Ability to work with both batch and real-time data processing
• Strong problem-solving skills and attention to detail
• Experience in the finance or banking industry is a strong advantage
• Fluent command of English and Polish, with excellent communication skills
Eligibility to work on this role:
Only candidates with an existing legal right to work in the European Union will be considered for this role.
#MAKEYourCareerBETTER
Interested? Apply now and include your CV in English or Polish, along with a statement confirming your consent to the processing and storage of your personal data.
🔍 Dekoder Ogłoszenia
🟡
Unleash the power of data to revolutionize finance — design the future of AI-driven financial infrastructures!
To bardzo marketingowy wstęp, który nie precyzuje konkretnych zadań ani technologii, a jedynie obiecuje duży wpływ i innowacyjność.
🔴
You will play a pivotal role in building reliable, scalable, and secure data systems that underpin next-generation AI applications in financial services.
Choć brzmi to ambitnie, "pivotal role" może oznaczać zarówno kluczowe zadania, jak i po prostu bycie częścią większego zespołu bez decyzyjności.
🟡
Your expertise will enable innovative solutions and empower data-driven insights that transform the industry.
Podobnie jak pierwszy punkt, jest to ogólne stwierdzenie o potencjalnym wpływie, które nie daje konkretnych informacji o codziennych obowiązkach.
🔴
Contribute to cloud-based data architecture and infrastructure management
Może oznaczać zarówno aktywne projektowanie architektury, jak i jedynie wsparcie w jej utrzymaniu lub wdrażaniu zmian.