Description

You will support the design, delivery, and enhancement of data infrastructure and analytics solutions within an Azure environment.

Responsibilities

• Develop and enhance data platform components using Azure Data Lake, Synapse, and Data Factory.
• Support data scientists by integrating machine learning models and setting up pipelines for data ingestion, model training, and deployment.
• Monitor and maintain ML pipelines in Azure Databricks to ensure models are properly deployed and updated.
• Collaborate with business teams in risk, finance, and compliance to translate data needs into technical requirements.
• Maintain the team backlog, document user stories, and participate in Agile/Scrum sprint sessions.
• Apply data governance and security practices within Azure cloud environments to meet regulatory requirements.

Required Skills

• 2–4 years of experience in data analytics, data science, or platform operations.
• Hands-on experience with Azure tools including Databricks, Data Factory, or Synapse Analytics.
• Proficiency in SQL and Python within a data platform or analytics context.
• Practical understanding of machine learning models, data pipelines, and model deployment lifecycles.
• Experience working within Agile/Scrum frameworks and managing backlogs.
• Knowledge of Azure Data Lake.
• Ability to communicate technical concepts to non-technical business stakeholders.

Preferred Skills

• Experience with dashboarding and reporting tools such as Power BI or Tableau.
• Exposure to MLflow, Azure ML, CI/CD, Git, or Terraform.
• Background in financial services, specifically regarding risk or compliance analytics.

Key Skills

Education

Any Gradute