Data Engineer

Job Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes to support business intelligence, analytics, and operational reporting.
• Build and optimize data integration workflows using tools such as Talend, Apache Airflow, SSIS, Pentaho, or similar technologies.
• Develop and manage data processing solutions using Python and SQL for large-scale structured and unstructured datasets.
• Design and maintain data warehouse and data lake architectures, including staging layers, transformation processes, and schema modelling.
• Monitor, troubleshoot, and optimize query performance and data processing efficiency to ensure reliable and high-performance data operations.
• Ensure data quality, consistency, integrity, and availability across enterprise systems and reporting platforms.
• Implement and maintain data security controls, including access management and least privilege principles for sensitive business data.
• Collaborate with cross-functional teams including IT, production, finance, and business stakeholders to understand data requirements and deliver effective solutions.
• Prepare and maintain technical documentation related to data pipelines, workflows, architecture, and operational procedures.
• Support real-time and operational data processing needs while ensuring SLA compliance and system reliability.
• Participate in system development lifecycle activities, including requirement analysis, development, testing, deployment, and post-implementation support.
• Analyze and resolve operational data issues while ensuring minimal disruption to business operations.

Qualifications

• Bachelor's degree in Information Technology, Computer Science, Data Engineering, or related field.
• Minimum 5 years of experience in Information Technology, with strong exposure to data engineering and data integration projects.
• Proficiency in Python and SQL for data processing, transformation, and analysis.
• Hands-on experience with ETL/ELT tools such as Talend, Apache Airflow, SSIS, Pentaho, or similar platforms.
• Strong understanding of data warehouse/data lake architecture, staging concepts, transformation processes, and schema modelling.
• Experience in optimizing query performance and handling large-scale data processing workloads.
• Basic understanding of data security practices and access control implementation.
• Strong analytical thinking and problem-solving skills, particularly in operational and real-time data environments.
• High attention to detail, accuracy, and discipline in handling sensitive and business-critical data.
• Effective communication and collaboration skills with cross-functional teams.
• Ability to work under operational pressure and meet pipeline delivery timelines according to SLA commitments.
• Experience in oil & gas or industrial operational environments is an advantage.