Data Engineer

Job Description

• Design and maintain scalable data pipelines that collect, transform and store business data.
• Build data models and datasets that make information easier for technology teams to access and use.
• Monitor data workflows, investigate failures and resolve issues to maintain reliable data delivery.
• Improve data quality by identifying incomplete, duplicate or inconsistent information and applying practical fixes.
• Develop and maintain data integrations between systems to support accurate information flow.
• Document data structures, pipeline logic and operational processes to support clear and consistent use.
• Work with technology colleagues to understand data needs and deliver fit-for-purpose solutions.
• Review existing data processes and implement improvements that strengthen performance and reliability.

MPI does not discriminate on the basis of race, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, or based on an individual's status in any group or class otherwise protected under applicable human rights legislation. MPI encourages applications from minorities, women, the disabled and all other qualified applicants

The Successful Applicant

Qualifications:

· Degree or Diploma in Computer Science, Data Engineering, Information Systems, or related field.

· 5+ years of experience as a Data Engineer or similar role.

· Proficiency in Python, PySpark, data modeling, ETL processes and data integration using Microsoft technologies.

· Advanced SQL skills for data transformation and querying on Azure data services (e.g., Data Factory, Databricks, Synapse, Fabric, Purview).

· Experience with SQL and debugging complex queries.

· Experience with Power BI or other BI tools.

· Familiarity with DevOps practices. CI/CD experience.

· Strong understanding of data pipeline engineering and big data design principles.

What's on Offer

* Opportunity to work with modern Azure data platforms and cloud-based engineering technologies.

* Exposure to large-scale data pipeline, data warehouse, and big data initiatives.

* Strong collaboration with engineering and operations teams on strategic projects.

* Ability to influence data quality, governance, security, and operational excellence.

* Continuous learning opportunities across Microsoft data technologies, DevOps practices, and analytics solutions.