Data and Machine Learning Architect

Domain: Banking & Finance
Experience: 10+ years
Project Duration: September 1, 2026 – June 29, 2027
Format: Remote
Location: Poland

About the Project

We are looking for a Data & Machine Learning Architect to join a greenfield initiative focused on building a next-generation, cloud-native digital banking platform.

The project aims to create a scalable, modular, API-first, event-driven, and AI-powered ecosystem supporting real-time operations, faster product innovation, and sustainable business growth.

The platform will leverage modern Microsoft Azure services, advanced data technologies, and machine learning capabilities to enable digital transformation at scale.

Responsibilities

• Define and design end-to-end data and machine learning architectures using Microsoft Azure
• Lead the design and implementation of modern data platforms covering data lakes, data warehouses, real-time streaming, and analytics
• 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
• Ensure data quality, security, regulatory compliance, reliability, and operational excellence across the platform
• Collaborate with business and technical stakeholders to translate business requirements into robust and scalable technology solutions
• Provide architectural guidance, technical leadership, and mentorship to engineering teams
• Evaluate emerging technologies and contribute to the strategic roadmap for data and AI capabilities

Requirements

• 10+ years of professional experience across Data Engineering, Data Architecture, Analytics, Artificial Intelligence, or Machine Learning
• Proven experience 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
• Strong hands-on programming skills with Python and SQL
• Experience with containerization and orchestration technologies such as Docker and Kubernetes
• Strong leadership, communication, collaboration, and stakeholder management skills
• Fluent business and technical English

Tech Stack

• Data Engineering
• Data Analysis
• AI / Machine Learning
• Microsoft Azure
• Azure Data Factory
• Azure Databricks
• Azure Synapse Analytics
• Azure Data Lake Storage
• Azure Machine Learning
• Azure DevOps
• CI/CD
• Python
• SQL
• Docker
• Kubernetes

Project Details

• Start date: September 2026
• Duration: 10 months
• Project type: Greenfield
• Verification process: Technical interview + project interview