Total 2 Senior Executive communications engineer job vacancies in The Philippines

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.

We are seeking a highly skilled and detail-oriented Senior Engineer to join our team. The Senior Engineer will be responsible for interpreting data, analyzing results using statistical techniques, and providing reports to help guide business decisions. This role involves collecting, processing, and analyzing large datasets, identifying trends, and providing actionable insights that help drive decision-making in the product development.

The ideal candidate is proficient in data manipulation and has strong analytical skills to transform raw data into meaningful insights. You will collaborate with various WD sites to understand their data needs and provide solutions to improve overall business performance.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Collect, clean, and organize large datasets from multiple sources, ensuring data accuracy and integrity.
• Extract and manipulate data from databases using SQL or other querying languages.
• Automate data collection processes where possible.
• Conduct deep-dive analysis using statistical and analytical techniques to identify trends, correlations, and patterns.
• Present data findings through dashboards, reports, and visualizations using tools like Spotfire, Power BI, or Excel.
• Communicate insights clearly and effectively to stakeholders, making data-driven recommendations.
• Work closely with cross-functional teams to understand business objectives and requirements.