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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.
Key Skills
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