~38m ago

ETIC, Fabric Data Engineer, Manager

Cairo - Eticmid

OtherEngineer Manager

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Quick Summary

Key Responsibilities

Design and implement scalable and secure data pipelines using Microsoft Fabric components (Data Factory in Fabric, Dataflows Gen2, Eventstreams, and Synapse Data Engineering).

Technical Tools

OtherEngineer Manager

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Technology

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Manager

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.

In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.

Key Responsibilities:

Design and implement scalable and secure data pipelines using Microsoft Fabric components (Data Factory in Fabric, Dataflows Gen2, Eventstreams, and Synapse Data Engineering).

Build and manage lakehouses and warehouses within OneLake, ensuring performance, scalability, and data governance compliance.

Collaborate with business and analytics teams to gather data requirements and translate them into reliable datasets for reporting and advanced analytics.

Develop and optimize notebooks (PySpark) for data transformation and machine learning workflows within Microsoft Fabric.

Support Power BI semantic models and implement real-time or near-real-time analytics.

Ensure data quality, lineage, and observability by leveraging Microsoft Purview or Fabric’s native monitoring capabilities.

Implement CI/CD pipelines and manage deployment of data assets using DevOps for Fabric artifacts.

Collaborate closely with data architects, analysts, and platform engineers to contribute to the modern data architecture roadmap.

Stay current with developments in Microsoft Fabric and related technologies to provide recommendations and continuous improvement.

Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
8+ years of experience in the Data & Analytics field

Proficiency in SQL, PySpark, and Power BI.

Experience with Microsoft OneLake, Dataflows Gen2, Synapse Engineering in Fabric, and DirectLake connectivity.

Familiarity with DataOps practices, version control (e.g., Git), and automated deployment pipelines.

Understanding of data modeling (dimensional/star schema) and performance optimization techniques.

Knowledge of data governance, security, and compliance within the Microsoft ecosystem.

Experience integrating data from diverse sources including APIs, flat files, relational and NoSQL databases.

Nice to Have

~1 min read

Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Hadoop, Azure Data Factory, Coaching and Feedback, Communication, Creativity, Data Anonymization, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline, Data Quality, Data Transformation {+ 24 more}