Designing, building, and maintaining scalable data pipelines and ETL/ELT workflows using Python, and Azure services.
Building analytics tools that use the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Managing data ingestion, orchestration, transformation, quality, and curation at scale.
Implementing and maintaining systems via event-driven architectures and APIs.
Collaborating closely with Data Scientists, product teams, and business stakeholders to translate data needs into robust solutions.
Ensuring high engineering standards: unit testing, mocking, CI/CD, code quality, repository structure, environment setup.
Providing technical guidance, code reviews, and mentoring to team members.

Bachelor's degree in computer science, software engineering, or comparable work experience
Proven experience working as an Data Engineer or related role
Solid hands-on experience with Azure infrastructure, including App Service, AI Services (Document Intelligence, AI Search, OpenAI services), Data Factory, Databricks, Azure Functions, Storage, Networking, Identity/RBAC and quota management
Experience implementing Infrastructure as Code (IaC) with Bicep
Strong background in reliability engineering, including monitoring, logging, troubleshooting and performance tuning
Proven experience in cloud cost optimization
Experience in Azure cloud architecture and best practices
Practical knowledge of CI/CD pipelines, preferably using GitHub Actions
Basic Python proficiency, including reading codebases and performing minor code modifications
Strong communication and analytical skills
Excellent English skills, both written and spoken
Strong understanding of data security and privacy best practices

Platform Data Engineer – Azure

Key skills