Data Engineer

About the Data Platform

We are building a robust Data & AI platform to drive smart insights, enable automation, and empower strategic decision-making across various business sectors.

We are seeking a passionate and skilled Data Engineer to join our growing team and help design, develop, and optimize our data infrastructure on Microsoft Azure.

Job Summary

The Data Engineer will play a key role in designing, building, and maintaining scalable data pipelines and solutions using the Azure ecosystem — with a strong focus on Azure Data Factory, Azure Databricks, PySpark, and Delta Lake.

This role involves close collaboration with the Head of Data & AI to implement efficient, secure, and high-performance data workflows that enable advanced analytics and AI-driven insights.

Key Responsibilities

• Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory and Azure Databricks.
• Implement data workflows leveraging PySpark and Delta Lake following Medallion Architecture principles.
• Build scalable and efficient data models and pipelines for both structured and unstructured data.
• Collaborate with Data Analysts, Data Scientists, and Business Stakeholders to deliver reliable data solutions.
• Ensure data quality, validation, and governance across all data pipelines.
• Optimize data performance, cost, and storage using Azure-native tools.
• Support AI/ML model deployment pipelines and integrate them into production workflows (a strong plus).
• Write clean, modular, testable, and well-documented Python code.
• Participate in architectural discussions, code reviews, and Agile ceremonies.
• Continuously identify and implement process improvements in data infrastructure and development workflows.

Key Qualifications

• 3+ years of experience in Data Engineering roles.
• Proven hands-on expertise with:
• Azure Data Factory (ADF)
• Azure Databricks
• Delta Lake / Lakehouse Architecture
• PySpark and distributed data processing
• SQL and Python
• Strong understanding of data warehousing, data modeling, and data governance best practices.
• Familiarity with CI/CD pipelines, version control (Git), and DevOps practices.
• Excellent communication, problem-solving, and collaboration skills.
• Eagerness to learn and contribute to a rapidly evolving Data & AI landscape.