Data Engineer (Azure)

TL;DR

Data Engineer (Azure): Designing and developing scalable data pipelines and data models within the Azure ecosystem with an accent on ETL/ELT processes and data lake architectures. Focus on integrating core business systems, ensuring data quality and governance, and collaborating with BI and Data Science teams.

Location: Remote options available

Company

hirify.global is an independent technology consulting firm providing guidance and solutions to businesses globally.

What you will do

• Design and develop data pipelines using Azure Data Factory and Azure Databricks.
• Integrate data from core insurance systems such as policies, claims, and customer platforms.
• Build and maintain data models in Azure Synapse and Azure Data Lake for analytics and reporting.
• Ensure data quality, governance, and traceability across the data platform.
• Collaborate with Data Science, BI, and business stakeholders to deliver data solutions.
• Contribute to best practices in data engineering, data governance, and data architecture.

Requirements

• 3+ years of experience working as a Data Engineer.
• Strong experience building and maintaining data pipelines using Azure Data Factory and Azure Databricks.
• Hands-on experience with Azure Synapse Analytics and Azure Data Lake.
• Strong programming skills in Python and SQL.
• Solid understanding of ETL/ELT processes, data modeling, and data lake architectures.
• Fluent English required.

Nice to have

• Experience in regulated environments such as insurance or finance.
• Spanish language proficiency.

Culture & Benefits

• Personalized career paths and regular salary assessments.
• Professional development through Technology Academy, Udemy, and company-paid certifications.
• Flexible policies and remote work options.
• Social benefits including transport and restaurant tickets, childcare support, and private health insurance.
• WeCare programme supporting employees in critical situations.

Hiring process

• Brief virtual or phone call to align on motivations and fit.
• Technical and cultural interviews (average of 3) with the line manager and team.
• Technical case study or assessment depending on the role's seniority.