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Coca-Cola HBC Logo Coca-Cola HBC · IT - Software Development

Senior Azure Data Engineer

Egypt, Cairo · Job Posted June 14, 2026
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Job Description

We are looking for a highly skilled and experienced Senior Azure Data Engineer with significant technical skills in Azure and strong business acumen to join our team in Coca-Cola Hellenic Digital & Technology Platform Services (DTPS) and be part of the Data Platforms team. You will have the opportunity to contribute to the strategy, design and development of our Enterprise and Operational Reporting, providing insights and supporting decision making for end users. The role involves significant collaboration with business and IT teams, opportunity to integrate and transform data from various data systems into structures that are suitable for building analytical solutions, design, develop and implement Azure-based solutions connecting certified and validated data sources to Power BI front-end visualizations - creating a single source of truth for reporting across CCH.

Job Responsibility

  • Design, build, and maintain scalable ELT/ETL pipelines using Azure Data Factory, ensuring reliability and performance at terabyte scale
  • Own end-to-end pipeline health: monitoring, alerting, incident response, and continuous improvement
  • Identify and resolve bottlenecks across ingestion, transformation, and serving layers
  • drive measurable performance gains
  • Contribute to the design and evolution of our medallion architecture and golden layer strategy
  • Implement data ingestion processes from multiple heterogeneous sources, ensuring accuracy, completeness, and consistency
  • Support the migration from SAP BW, ensuring data continuity and quality throughout
  • Ensure data integrity and availability through appropriate storage solutions, partitioning strategies, and access controls
  • Work autonomously to deliver complex data engineering tasks with minimal supervision, while proactively communicating progress and blockers
  • Collaborate closely with data scientists, BI analysts, and business stakeholders to understand requirements and translate them into technical solutions
  • Participate in agile ceremonies, contribute to sprint planning, and own your backlog items end-to-end

Requirements

  • Bachelor's degree in Information Technology, Computer Science, or related field
  • 5+ years of experience in data engineering with a strong focus on Azure (Azure Data Factory, Azure Data Lake Storage, Fabric)
  • Proven experience designing and building production-grade data pipelines that handle large volumes of data reliably
  • Strong SQL skills and experience with data modelling, schema design, and query optimization
  • Hands-on experience with Databricks (PySpark / Spark SQL) for large-scale data transformation
  • Proficiency in at least one programming language: Python (preferred), Scala, or C#/.NET
  • Solid understanding of data warehouse and lakehouse concepts
  • Strong ability to work independently, manage your own priorities, and deliver under ambiguity
  • Excellent communication skills - able to translate technical concepts for business stakeholders and vice versa
  • Excellent problem-solving and debugging skills
  • Excellent spoken and written English
  • Communication, organizational and analytical skills

Nice to have

  • Experience with real-time or near-real-time streaming pipelines (Azure Event Hubs, Apache Kafka, Spark Streaming)
  • Hands-on experience with CI/CD for data pipelines using Azure DevOps, Git, and infrastructure-as-code (Terraform)
  • Familiarity with DevSecOps principles and experience working within the SAFe Agile framework
  • Knowledge of SAP BW (extractors, transformations, queries, data export) and experience supporting BW migrations
  • Experience with big data technologies such as Hadoop, Spark, and Hive, and large data volume management
  • Strong analytical and problem-solving mindset - you enjoy finding root causes, not just symptoms
  • Experience with Power BI and DAX for building analytical models and connecting to enterprise data
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