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