Data Engineer

Workload — tbd
Duration — 10 months
Location — Poland

Banking and Finance Job Details Technical 

Requirements: 

10+ years of professional experience across Data Engineering, Data Architecture, Analytics, Artificial Intelligence, or Machine Learning.

- Demonstrated track record of designing and delivering enterprise

-scale data and machine learning platforms within the Microsoft Azure ecosystem. 

- Advanced knowledge of Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake Storage, Azure Machine Learning, AKS, and Azure DevOps. 

- Practical experience implementing MLOps practices, including ML lifecycle management, model governance, monitoring, and CI/CD automation. 

- Strong understanding of machine learning workflows, feature engineering, model deployment, and responsible AI principles. 

- Solid expertise in data governance, security, regulatory compliance, and metadata management. 

- Proficiency in Python and SQL, with strong hands-on programming capabilities. 

- Experience working with containerization and orchestration technologies such as Docker and Kubernetes. 

- Strong leadership, communication, collaboration, and stakeholder management skills. 

- Fluent business and technical English Required 

Technical Skills: 

- Data Engineering 

- Data analysis 

- AI - Machine learning 

- Microsoft Azure 

- Azure Data Factory 

- Azure Devops 

- Microsoft Azure Synapse 

- CI/CD - Python - SQL - Docker 

- Kubernetes 

Main Responsibilities: 

- Define and design end-to-end data and machine learning architectures using Microsoft Azure.

 - Lead the design and implementation of modern data platforms encompassing data lakes, data warehouses, real-time streaming, and analytics capabilities. 

- Develop scalable ML pipelines covering data ingestion, model training, deployment, monitoring, and automated retraining. 

- Establish MLOps practices, CI/CD standards, governance frameworks, and best practices across data and AI environments. 

- Drive data quality, security, compliance, reliability, and operational excellence across the platform. 

- Partner with business and technical stakeholders to translate business needs into robust, scalable technology solutions. 

- Provide architectural direction, technical leadership, and mentorship to engineering teams. 

- Assess emerging technologies and contribute to the strategic evolution and roadmap of data and AI capabilities. 

About the project Greenfield project Selected specialist will join a greenfield initiative dedicated to developing a next-generation, cloud-native digital banking platform. The program focuses on creating a scalable, modular, API-first, event-driven, and AI-powered ecosystem designed to enable real-time operations, accelerate product innovation, and support sustainable business growth. 

The platform leverages modern Azure services, advanced data technologies, and machine learning capabilities to drive digital transformation at scale. Important: If a candidate successfully completes the recruitment process, they will be required to undergo an identification verification prior to employment. 

This process will include, but is not limited to, a one-time online inspection of a government-issued photo ID, such as a valid ID card, driver’s license, or passport. Client has the right to require MTA (Mandatory Time Away) for up to 10 days per year (usually in December)