Total 2 Senior Executive software engineer job vacancies in The Philippines

Octal Philippines Inc. is looking for a Senior Software Engineer to join our dynamic and innovative engineering team. In this role, you will be responsible for designing, developing, and maintaining high-quality software solutions that meet our clients’ needs. You will collaborate with cross-functional teams to deliver impactful products and contribute to the overall architecture and technical direction of our projects.

• 5+ years of technical leadership experience, with a proven track record of leading successful engineering teams.
• Proficiency in Python and strong experience with Golang. Deep understanding of building and maintaining integrations.
• Stellar communication skills, both verbal and written, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Experience in hiring, coaching, and mentoring engineers, with a passion for helping others grow and succeed.
• Strong proficiency in AWS, with experience designing and maintaining cloud infrastructure.
• Ability to interface effectively with cross-functional teams, fostering a collaborative and aligned engineering culture.

Develops and implements scalable data pipelines, transforms complex datasets into actionable insights, and creates data-driven solutions to support strategic decision-making and business growth.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• Design, build, and maintain robust data pipelines for collecting, processing, and integrating data from various sources.
• Ensure that data is accurately and efficiently transferred and transformed between systems.
• Create dashboards, reports, and visualizations to support decision-making.
• Collaborate with cross-functional teams to understand their data needs and provide actionable, data-driven recommendations.
• Use statistical, machine learning, or deep learning techniques to analyze and model data, identify trends, patterns, and relationships, and provide applicable solutions.
• Develop predictive models using machine learning algorithms to forecast trends and future outcomes. Then, deploy these models and systems, and monitor and maintain them to ensure they are working effectively.
• Document data workflows, processes, and technical specifications.
• Stay updated with industry trends and best practices to continuously improve data engineering practices.