Data Platform Engineer/ Data Engineer

Key Responsibilities

• Design, construct, and maintain scalable data ingestion and processing workflows using Apache Airflow.
• Manage, optimize, and expand enterprise Data Lake infrastructure to ensure high availability, performance, and data integrity.
• Maintain and deploy containerized data services and pipeline workloads on Kubernetes clusters.
• Integrate DevOps best practices, automated CI/CD pipelines, and infrastructure management across data platforms.
• Monitor data pipeline health, troubleshoot production incidents, and perform root-cause analysis to ensure continuous operational uptime.
• Collaborate closely with data scientists, business analysts, and IT infrastructure teams to refine data integration capabilities.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Software Engineering, or a related discipline.
• 2 to 4 years of hands-on experience in data engineering, data platform engineering, or DevOps roles.
• Strong, hands-on expertise with Apache Airflow for workflow orchestration and pipeline management.
• Proven experience managing and optimizing Data Lake architectures.
• Working knowledge of Kubernetes and containerization technologies (Docker).
• Practical experience with DevOps methodologies, CI/CD tools, and automated deployment pipelines.
• Proficiency in Python, SQL, and Shell scripting for system automation and data processing.
• Good communication, problem-solving, and analytical skills.

Desirable Qualifications

• Experience working within financial institutions, banking environments, or public sector bodies.
• Exposure to cloud platforms (AWS, Azure, GCP) or hybrid cloud infrastructure.