Our client is a pioneering maritime AI company offering a comprehensive platform for risk management and maritime domain awareness. With advanced technology and extensive industry expertise, we help organizations overcome maritime challenges, predict future events,and drive success. Windward’s AI-powered solution allows stakeholders to make real-time, predictive intelligence-driven decisions, providing a 360° view of the maritime ecosystem.
As a Senior Data Engineer, you will hold a crucial role in designing, developing, and maintaining our data platform, supporting critical data-driven decision-making processes across the organization. You will collaborate closely with cross-functional teams, including data scientists,analysts, and software engineers, ensuring the smooth flow of data and optimizing data pipelines. The ideal candidate will possess a strong background in data engineering, with proven expertise in Kafka, Java (including Spring Boot), Data Pipelines, AWS, and ETL processes. Familiarity with Python, NodeJS, and a willingness to challenge decisions, work independently, and mentor junior team members will be highly valued.
- Lead the design, development, and maintenance of efficient and scalable data pipelines, facilitating data collection, processing, and transformation from diverse sources
- Implement real-time data streaming solutions using Kafka, ensuring timely data ingestion and availability
- Utilize Java, including Spring Boot, to build robust and high-performance data processing applications within our data platform
- Collaborate closely with cross-functional teams to comprehend data requirements, identify opportunities for data optimization, and support data-driven initiatives
- Uphold data integrity, reliability, and availability by implementing effective ETL processes and conducting data quality checks
- Leverage AWS services for data storage, processing, and analytics, adhering to security and performance best practices
- Monitor and troubleshoot data pipeline performance, proactively identifying bottlenecks and implementing optimizations
- Create comprehensive documentation for data engineering processes, best practices, and internal guidelines
- Stay updated with industry trends and emerging technologies in data engineering, contributing to continuous improvement