Description

We are seeking a highly motivated and experienced Data Engineer to join our growing Technology team. This role is ideal for a data engineering professional with strong expertise in designing, building, and optimizing scalable data solutions, ETL pipelines, and modern cloud-based analytics platforms. The successful candidate will play a key role in developing and maintaining enterprise-grade data ecosystems that support business intelligence, analytics, and data-driven decision-making for global clients

Job Responsibilities

• Design, develop, and maintain scalable and reliable data pipelines and ETL/ELT processes.
• Build and optimize data integration and transformation workflows using Azure Synapse Analytics, Azure Data Factory (ADF), and PySpark.
• Develop and manage data lake architectures using Azure Data Lake Storage (ADLS) and related Azure services.
• Collaborate closely with Data Engineers, Data Scientists, Analysts, and business stakeholders to understand data requirements and deliver effective solutions.
• Design and implement robust data models to support reporting, analytics, and advanced data processing needs.
• Ensure data quality, integrity, security, and compliance with organizational standards and regulatory requirements.
• Monitor, troubleshoot, and resolve data pipeline, integration, and analytics platform issues.
• Optimize data processing performance and scalability across cloud-based environments.
• Participate in architecture discussions and contribute to the continuous improvement of data engineering best practices and standards.
• Create and maintain technical documentation for data solutions, processes, and workflows.

Required Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field.
• 3–5 years of hands-on experience in Data Engineering.
• Strong experience with Azure Synapse Analytics and Azure Data Factory (ADF).
• Solid understanding of ETL/ELT methodologies, data warehousing concepts, and data modeling techniques.
• Experience working with PySpark for large-scale data transformation and processing.
• Practical experience with Azure Data Lake Storage (ADLS) and modern data lake architectures.
• Strong SQL skills and experience working with structured and unstructured data.
• Understanding of data governance, data quality management, security, and compliance best practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and stakeholder management abilities.

Preferred Qualifications

• Experience with Informatica for data integration and ETL development.
• Familiarity with cloud-based analytics and data platform services within the Azure ecosystem.
• Knowledge of CI/CD practices, DevOps methodologies, and data pipeline automation.
• Exposure to big data technologies and modern data engineering frameworks.