Azure Data Engineer

Alldus International Consulting Ltd; Dublin; Remote; EUR 60,000 - 80,000; Full time

Job summary

A global life sciences company is seeking an experienced Azure Data Engineer to join the team remotely. This role focuses on building data pipelines and applying machine learning to enhance patient recruitment and financial planning. The ideal candidate will have strong experience with Azure tools, ETL processes, and clinical trial data.

Qualifications

• Proficiency in Azure Data Factory, Azure Synapse or Azure Databricks.
• Strong experience with ETL processes and data pipeline development.
• Familiarity with machine learning and predictive analytics.

Responsibilities

• Build and maintain scalable data pipelines using Azure tools.
• Gather and integrate data from clinical systems.
• Develop and train machine learning models for forecasting.

Skills

Azure Data Factory

ETL processes

Machine learning

Predictive analytics

Clinical trial data

Tools

Azure Synapse

Azure Databricks

Job description

Azure Data Engineer

Location: Remote Ireland / EU
Contract Type: Initial 5 months (potential extension)
Start Date: ASAP

Our client, a global life sciences company, are hiring an experienced Azure Data Engineer to to join the team remotely on an initial five-month contract. The successful candidate will be responsible for building data pipelines, integrating complex clinical systems, and applying machine learning to improve prediction accuracy for patient recruitment and financial planning.

Responsibilities

• Build and maintain scalable data pipelines using Azure tools.
• Gather and integrate data from clinical systems (CTMS, EDC, financial platforms).
• Develop and train machine learning models for forecasting patient recruitment and investigator fees.
• Collaborate with cross-functional teams to deliver strategic data solutions.
• Ensure high data quality and performance across the pipeline.

Skillset

• Proficiency in Azure Data Factory, Azure Synapse or Azure Databricks.
• Strong experience with ETL processes and data pipeline development.
• Knowledge of clinical trial data and complex data mappings.
• Familiarity with machine learning and predictive analytics.
• Domain expertise in systems such as CTMS, EDC and study planning tools.