Senior Data Engineer - 1

About Metayb

Role Overview

Key Responsibilities

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

Qualifications

• 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.

Technical Skills

Mandatory Skills

• 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.

Preferred Skills

• 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.