Data Engineer - 2

About Metayb

Metayb is a fast-growing digital transformation company empowering organizations to thrive in the digital-first era. In just three years, we've built a team of 500+ experts focused on creating seamless customer experiences, boosting operational efficiency, and delivering actionable insights. Our core strengths include Digital Transformation, Data Science, SAP Implementation, Workflow Automation, Finance, and Supply Chain Services, with aspirations to expand into IoT, AI/ML, and Virtual Reality.

By leveraging emerging technologies, Metayb aims to be a trusted global partner in delivering impactful, future-ready solutions.

Role Overview

As a Senior Data Engineer, you will be responsible for designing, developing, and maintaining scalable data solutions that enable business intelligence, analytics, and data-driven decision-making. You will work closely with business stakeholders, data analysts, and technology teams to build robust data pipelines, optimize data architectures, and ensure the availability, quality, and security of enterprise data assets.

The ideal candidate will possess strong expertise in modern data engineering practices, cloud-based data platforms, and large-scale data processing frameworks, with hands-on experience in Microsoft Fabric and Azure data services.

Key Responsibilities

• Data Engineering & Pipeline Development
• Design, develop, and maintain scalable data pipelines and ETL/ELT processes to support analytics and reporting requirements.
• Build and optimize data ingestion frameworks for structured, semi-structured, and unstructured data sources.
• Develop efficient data models and architectures that support enterprise-wide reporting and analytics initiatives.
• Ensure data systems are scalable, secure, reliable, and capable of handling large volumes of data.
• Data Architecture & Platform Management
• Design and implement modern data architectures aligned with business and technology objectives.
• Manage and optimize cloud-based data platforms, data warehouses, and lakehouse environments.
• Collaborate with solution architects and business teams to translate requirements into scalable technical solutions.
• Drive best practices in data governance, security, and performance optimization.
• Data Quality & Governance
• Implement data quality checks, validation frameworks, and monitoring mechanisms to ensure data accuracy and integrity.
• Establish standards and processes for data management, lineage, and governance.
• Troubleshoot and resolve data inconsistencies, performance bottlenecks, and system issues.
• Ensure compliance with organizational and regulatory data management standards.
• Analytics Enablement & Business Support
• Work closely with business intelligence, analytics, and data science teams to enable advanced reporting and insights generation.
• Analyze complex datasets to identify trends, patterns, and opportunities that support strategic business decisions.
• Support the development of dashboards, KPIs, and self-service analytics capabilities.
• Provide technical guidance and recommendations to stakeholders on data-related initiatives.
• Innovation & Continuous Improvement
• Stay updated with emerging technologies, tools, and trends in data engineering, cloud analytics, and big data ecosystems.
• Evaluate and recommend new technologies that enhance scalability, efficiency, and business value.
• Drive automation and process improvements to improve data delivery and operational excellence.
• Contribute to the continuous evolution of Metayb’s data engineering capabilities and best practices.
  
  

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
• 5 – 8 years of relevant experience in Data Engineering, Data Warehousing, or Analytics Engineering.
• Minimum 1+ year of hands-on experience with Microsoft Fabric is mandatory.
• Strong experience working with Azure data services and cloud-based data platforms.
• Strong understanding of data engineering principles including data modeling, ETL/ELT frameworks, data warehousing, and big data processing.
• Proficiency in SQL and Python for data engineering and analytics use cases.
• Experience designing and implementing scalable data architectures and data integration solutions.
• Strong analytical and problem-solving skills with the ability to manage complex technical challenges.
• Excellent communication and stakeholder management skills.
• High attention to detail and commitment to delivering high-quality, reliable solutions.
  
  

• Microsoft Fabric (Minimum 1+ year of hands-on experience).
• Azure Data Services and Cloud Data Platforms.
• SQL Development and Query Optimization.
• Python Programming.
• Data Modeling and Data Warehousing.
• ETL/ELT Pipeline Development.
• Data Integration and Data Quality Management.
  
  

• Databricks.
• Azure Data Factory (ADF).
• Azure Data Lake Storage (ADLS).
• Synapse Analytics.
• Power BI.
• Big Data Processing Frameworks and Lakehouse Architectures.
• Data Governance and Security Best Practices.