Data Engineer: Azure & Fabric Pipelines for Global Impact

HSO Group B.V.

México

On-site

MXN 600,000 - 900,000

Full time

14 days+

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Benefits offered by this job

Global exposure

Microsoft certification exams

Learning & Development sessions

Career growth opportunities

Competitive compensation

Job summary

HSO Group B.V. is seeking a proactive Data Engineer to design, build, and optimize modern data platforms using Microsoft Fabric and Azure.

You will collaborate with international teams to deliver scalable, secure data solutions, with opportunities for AI-assisted development tools and Microsoft certification exams. This role offers global exposure and a path for technical growth within a leading Microsoft partner.

Qualifications

Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
3+ years of experience in data engineering.
Hands-on experience with Microsoft Fabric (required).
Strong programming skills in Python and PySpark.
Strong knowledge of SQL and data modelling principles.
Experience designing and building modern data pipelines and ETL/ELT processes.
Experience with Azure Data Factory (ADF) and data integration solutions.
Experience with Azure data technologies and cloud-based data platforms.
Familiarity with Data Lake, Lakehouse, and Data Warehouse concepts.
Experience with Git, CI/CD pipelines, and DevOps practices.
Experience using AI-assisted development tools such as GitHub Copilot, Microsoft Copilot, or similar solutions.
Strong analytical and problem-solving skills.
Excellent communication skills and the ability to work in a collaborative, international environment.

Responsibilities

Design, develop, and maintain scalable data solutions using Microsoft Fabric, Azure Data Factory, and Azure technologies.
Build, maintain, and optimize data pipelines using Python, PySpark, SQL, Microsoft Fabric, and Azure Data Factory.
Develop and support ETL/ELT processes, data integration workflows, and orchestration solutions.
Work with structured and unstructured data from multiple sources.
Implement and maintain data models that support reporting, analytics, and AI workloads.
Ensure data quality, governance, security, and compliance across data platforms.
Monitor, troubleshoot, and optimize data pipelines, workflows, and platform performance.
Collaborate with consultants, architects, and client stakeholders to deliver business-driven data solutions.
Leverage AI-assisted development tools to improve productivity and code quality.
Contribute to continuous improvement of engineering standards, best practices, and technical documentation.
Support CI/CD processes and automated deployment of data solutions.