
āļŠāļģāļāļąāļāļāļēāļāļāļāļŦāļĄāļēāļĒ āļāļĢāļĩāļŠāļļāļāļāļāđ āļāļāļēāļĒāļāļ§āļēāļĄāđāđāļĨāļ°āļāļļāļĢāļāļīāļ
āđāļĄāđāļĄāļĩāļāļģāđāļŦāļāđāļāļāļēāļāļŠāļģāļŦāļĢāļąāļāļāļĢāļīāļĐāļąāļāļāļĩāđ āļāđāļāđāļāļāļĩāđāđāļāđāļāļāļģāđāļŦāļāđāļāļāļēāļāļāļĩāđāļāļļāļāļāļēāļāļāļ°āļŠāļāđāļ
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
2 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
English, Thai
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
- Supervising quality of all content (Candidate and HR).
- Ensuring all content align to high standards.
- Vertical Media Management.
- Vertical Videos and Office Highlights.
- Vertical Video Podcasts for EB clients, with clients' HR personnel..
- Transforming traditional content into engaging vertical formats for our mobile-first audiences.
- Written Content Oversight.
- Supervising writing content articles for all our EB clients (articles, Office Highlights etc.).
- Crafting compelling narratives that showcase company cultures and employee experiences.
- Podcast Management.
- Executing creation of HR related WorkVenture Podcasts.
- To demonstrate our expertise in Employer Branding and to enable showcase for our clients..
- Executing creation of Candidate Related Podcasts.
- Building thought leadership through authentic conversations about workplace trends.
- Social Media Content Development.
- Finding new ideas and producing candidate & B2B HR content.
- Maintaining our TikTok, Facebook, and LinkedIn presence.
- Creating vertical and horizontal format content.
- Staying ahead of social media trends to keep the content fresh and engaging.
- Creativity.
- Exceptional creative thinking and innovative approach to content.
- Ability to generate fresh ideas that capture audience attention.
- Talent for visual storytelling across different media formats.
- Organizational Skills.
- Outstanding project management abilities to handle multiple content streams.
- Excellence in planning, prioritizing, and meeting deadlines.
- Additional Requirements.
- Experience in content creation & management (2+ years preferred).
- Proficiency with digital content creation tools.
- Strong communication and team collaboration skills.
- Ability to adapt quickly to changing trends and audience preferences.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
2 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
Sales, Industry trends, Business Development
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Market Development: Proactively identify and cultivate relationships with local panel builders to generate demand for Siemens Sinova Products.
- Product Promotion: Introduce and promote Sinova products, including MCCBs, MCBs, ACBs, and Contactors, to panel builders, emphasizing their technical superiority and advantages in panel construction.
- Technical Support: Provide comprehensive technical assistance to panel builders, including product specifications, installation guidance, and troubleshooting support to ...
- Offer Creation: Collaborate with the sales team to develop customized offers and proposals tailored to the specific needs and requirements of panel builders, highlighting the value proposition of Sinova products.
- Relationship Management: Build and maintain strong relationships with panel builders, serving as a trusted advisor and resource for all their technical and product-related inquiries.
- Training and Education: Conduct training sessions and workshops for panel builders to enhance their understanding of Sinova products and their applications, thereby empowering them to leverage these products effectively.
- Market Intelligence: Stay abreast of industry trends, competitor activities, and market developments to identify new opportunities and inform strategic decision-making.
- Bachelor's degree in Electrical Engineering, or related field experience.
- Minimum of 2-5 years of experience in sales or business development within the electrical industry, preferably in a technical capacity.
- In-depth knowledge of electrical distribution systems and components, with a focus on MCCBs, MCBs, ACBs, and Contactors.
- Strong technical aptitude and ability to articulate complex technical concepts in a clear and concise manner.
- Proven track record of successfully building and managing relationships with customers and partners.
- Excellent communication, negotiation, and presentation skills.
- Self-motivated, proactive, and results-oriented with a strong commitment to achieving sales targets and driving business growth.
- Willingness to travel locally to meet with panel builders and attend industry events as needed.
- Want to learn more about us?.
- Siemens is the innovation and technology leader in industrial automation and digitalization. Together with our partners and customers we drive Digitalization in both the discrete and the process industry, enabling flexibility, efficiency, and reduced time to market.
āļāļąāļāļĐāļ°:
Compliance, Legal, Risk Management
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Establish and maintain appropriate security measures for personal data protection to prevent unauthorized access, loss, alteration, or disclosure..
- Regularly review and update security measures to align with technological advancements and PDPA requirements..
- Ensure third-party vendors handling personal data comply with data protection regulations..
- Implement and oversee data retention and deletion processes per legal requirements..
- Develop a risk management system for PDPA compliance..
- Assess risks related to personal data processing, evaluate mitigation strategies, and audit IT systems for security compliance..
- Conduct periodic assessments of IT systems handling personal data..
- Evaluate the effectiveness of data protection measures in databases, applications, and information security frameworks..
- Bachelor s degree in Computer Science, IT Security, Management Information Systems, or a related field.
- 5-10 years of experience in Database Management, IT Security, or Data Privacy Compliance.
- Proficiency in database management (SQL Server, MySQL).
- Understanding of IT security, data governance or compliance frameworks.
- Location: BTS Ekkamai
- Working Day: Mon-Fri.
āļāļĢāļ°āļŠāļāļāļēāļĢāļāđ:
5 āļāļĩāļāļķāđāļāđāļ
āļāļąāļāļĐāļ°:
English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ30,000+
- Bachelor/Master degree in Accounting, Finance or relating fields.
- Have working experience in financial services at least 5 years in regulatory reporting of Banking industry.
- Strong understanding in regulatory regulations and banking products.
- Dealing with other departments for acquiring information.
- Proficiency in financial software and Microsoft Excel, Word and PowerPoint.
- Strong communication in both Thai and English.
- Attention to detail and a commitment to accuracy.
- Remark: The Bank requires the verification of criminal records prior consideration for employment to ensure secured and maintain standards of the organization.
āļāļąāļāļĐāļ°:
Compliance, Research, Automation
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- DataOps, MLOps, and AIOpsDesign, build, and optimize scalable, secure, and efficient data pipelines for AI/ML workflows.
- Automate data ingestion, transformation, and deployment across AWS, GCP, and Azure.
- Implement MLOps and AIOps for model versioning, monitoring, and automated retraining.
- Ensure performance, security, scalability, and cost efficiency in AI lifecycle management.
- Performance Optimization & SecurityMonitor, troubleshoot, and optimize AI/ML pipelines and data workflows to enhance reliability.
- Implement data governance policies, security best practices, and compliance standards.
- Collaborate with cybersecurity teams to address vulnerabilities and ensure data protection.
- Data Engineering & System IntegrationDevelop and manage real-time and batch data pipelines to support AI-driven applications.
- Enable seamless integration of AI/ML solutions with enterprise systems, APIs, and external platforms.
- Ensure data consistency, quality, and lineage tracking across the AI/ML ecosystem.
- AI/ML Model Deployment & OptimizationDeploy and manage AI/ML models in production, ensuring accuracy, scalability, and efficiency.
- Automate model retraining, performance monitoring, and drift detection for continuous improvement.
- Optimize AI workloads for resource efficiency and cost-effectiveness on cloud platforms.
- Continuous Learning & InnovationStay updated on AI/ML advancements, cloud technologies, and big data innovations.
- Contribute to proof-of-concept projects, AI process improvements, and best practices.
- Participate in internal research, knowledge-sharing, and AI governance discussions.
- Cross-Functional Collaboration & Business UnderstandingWork with business teams to ensure AI models align with organizational objectives.
- Gain a basic understanding of how AI/ML supports predictive analytics, demand forecasting, automation, personalization, and content generation.
- Bachelor s degree in Computer Science, Data Engineering, Information Technology, or a related field. Advanced degrees or relevant certifications (e.g., AWS Certified Data Analytics, Google Professional Data Engineer, Azure Data Engineer) are a plus.
- Experience:Minimum of 3-5 years experience in a data engineering or operations role, with a focus on DataOps, MLOps, or AIOps.
- Proven experience managing cloud platforms (AWS, GCP, and/or Azure) in a production environment.
- Hands-on experience with designing, operating, and optimizing data pipelines and AI/ML workflows.
- Technical Skills:Proficiency in scripting languages such as Python and Bash, along with experience using automation tools.
- Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes) is desirable.
- Strong knowledge of data processing frameworks (e.g., Apache Spark) and data pipeline automation tools.
- Expertise in data warehouse solutions and emerging data lakehouse architectures.
- Experience with AWS technologies is a plus, especially AWS Redshift and AWS SageMaker, as well as similar tools on other cloud platforms.
- Understanding of machine learning model deployment and monitoring tools.
āļāļąāļāļĐāļ°:
SAS, SQL, Python
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āļ§āļļāļāļīāļāļēāļĢāļĻāļķāļāļĐāļēāļĢāļ°āļāļąāļāļāļĢāļīāļāļāļēāļāļĢāļĩāļāļķāđāļāđāļ āļāđāļēāļāļāļēāļĢāļāļąāļāļāļĩ āđāļĻāļĢāļĐāļāļĻāļēāļŠāļāļĢāđ āļŠāļāļīāļāļī MIS āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļāļāļĄāļāļīāļ§āđāļāļāļĢāđ āļ§āļīāļāļĒāļēāļāļēāļĢāļāļāļĄāļāļīāļ§āđāļāļāļĢāđ āļāļēāļĢāđāļāļīāļ āļāļĢāļīāļŦāļēāļĢāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļ āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļāļēāļĢāđāļāļīāļ āļŦāļĢāļ·āļāļŠāļēāļāļēāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđ āļāđāļēāļāļāļĢāļīāļŦāļēāļĢāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļāđāļēāļāļŠāļīāļāđāļāļ·āđāļ āļŦāļĢāļ·āļāļāļĢāļīāļŦāļēāļĢ Portfolio āļŦāļĢāļ·āļāļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ āļāļĒāđāļēāļāļāđāļāļĒ 3 āļāļĩ.
- āļŠāļēāļĄāļēāļĢāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāļŦāļĢāļ·āļāļāļĢāļ°āđāļĄāļīāļāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļ āđāļāļ·āđāļāđāļŦāđāļŠāļāļāļāļĨāđāļāļāļāļąāļāļāļļāļāļ āļēāļāļāļāļāļŠāļīāļāđāļāļ·āđāļāđāļĨāļ°āđāļāđāļēāļŦāļĄāļēāļĒāļāļāļāļāļāļāđāļāļĢ.
- āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāļāđāļēāļāļāļĨāļīāļāļ āļąāļāļāđāļŠāļīāļāđāļāļ·āđāļāļĢāļēāļĒāļĒāđāļāļĒ āđāļĨāļ°āļāļĢāļ°āļāļ§āļāļāļīāļāļēāļĢāļāļēāļŠāļīāļāđāļāļ·āđāļāļĢāļēāļĒāļĒāđāļāļĒ.
- āļŠāļēāļĄāļēāļĢāļāļāļģāđāļŠāļāļāđāļĨāļ°āļŠāļ·āđāļāļŠāļēāļĢāđāļāđāļāļĩ.
- āļŠāļēāļĄāļēāļĢāļāđāļāđāļ āļēāļĐāļēāļāļąāļāļāļĪāļĐāđāļāđāđāļāļĢāļ°āļāļąāļāļāļĩ.
- āļŠāļēāļĄāļēāļĢāļāđāļāđāđāļāļĢāđāļāļĢāļĄ SAS, SQL, MS āđāļāļīāļāļĨāļķāļ āđāļĨāļ° Python āđāļāđāļāļāđāļ.
- āļāđāļēāļāļŠāļēāļĄāļēāļĢāļāļāđāļēāļāđāļĨāļ°āļĻāļķāļāļĐāļēāļāđāļĒāļāļēāļĒāļāļ§āļēāļĄāđāļāđāļāļŠāđāļ§āļāļāļąāļ§āļāļāļāļāļāļēāļāļēāļĢāļāļĢāļļāļāđāļāļĒ āļāļģāļāļąāļ (āļĄāļŦāļēāļāļ) āļāļĩāđ https://krungthai.com/th/content/privacy-policy āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāđāļĄāđāļĄāļĩāđāļāļāļāļēāļŦāļĢāļ·āļāļāļ§āļēāļĄāļāļģāđāļāđāļāđāļāđ āļāļĩāđāļāļ°āļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ āļĢāļ§āļĄāļāļķāļāļāđāļāļĄāļđāļĨāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļĻāļēāļŠāļāļēāđāļĨāļ°/āļŦāļĢāļ·āļāļŦāļĄāļđāđāđāļĨāļŦāļīāļ āļāļķāđāļāļāļēāļāļāļĢāļēāļāļāļāļĒāļđāđāđāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļāļāļāļāļāđāļēāļāđāļāđāļāļĒāđāļēāļāđāļ āļāļąāļāļāļąāđāļ āļāļĢāļļāļāļēāļāļĒāđāļēāļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāđāļāđ āļĢāļ§āļĄāļāļķāļāļŠāļģāđāļāļēāļāļąāļāļĢāļāļĢāļ°āļāļģāļāļąāļ§āļāļĢāļ°āļāļēāļāļ āļŦāļĢāļ·āļāļāļĢāļāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§āļŦāļĢāļ·āļāļāđāļāļĄāļđāļĨāļāļ·āđāļāđāļ āļāļķāđāļāđāļĄāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļŦāļĢāļ·āļāđāļĄāđāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļŠāļĄāļąāļāļĢāļāļēāļāđāļ§āđāļāļāđāļ§āđāļāđāļāļāđ āļāļāļāļāļēāļāļāļĩāđ āļāļĢāļļāļāļēāļāļģāđāļāļīāļāļāļēāļĢāđāļŦāđāđāļāđāđāļāļ§āđāļēāđāļāđāļāļģāđāļāļīāļāļāļēāļĢāļĨāļāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļāļāđāļŦāļ§ (āļāđāļēāļĄāļĩ) āļāļāļāļāļēāļāđāļĢāļāļđāđāļĄāđāđāļĨāļ°āđāļāļāļŠāļēāļĢāļāļ·āđāļāđāļāļāđāļāļāļāļĩāđāļāļ°āļāļąāļāđāļŦāļĨāļāđāļāļāļŠāļēāļĢāļāļąāļāļāļĨāđāļēāļ§āđāļ§āđāļāļāđāļ§āđāļāđāļāļāđāđāļĨāđāļ§āļāđāļ§āļĒ āļāļąāđāļāļāļĩāđ āļāļāļēāļāļēāļĢāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļāđāļāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāļāļļāļāļāļĨāđāļāđāļēāļāļģāļāļēāļ āļŦāļĢāļ·āļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļļāļāļŠāļĄāļāļąāļāļī āļĨāļąāļāļĐāļāļ°āļāđāļāļāļŦāđāļēāļĄ āļŦāļĢāļ·āļāļāļīāļāļēāļĢāļāļēāļāļ§āļēāļĄāđāļŦāļĄāļēāļ°āļŠāļĄāļāļāļāļāļļāļāļāļĨāļāļĩāđāļāļ°āđāļŦāđāļāļģāļĢāļāļāļģāđāļŦāļāđāļ āļāļķāđāļāļāļēāļĢāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ·āđāļāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄāļāļāļāļāđāļēāļāļĄāļĩāļāļ§āļēāļĄāļāļģāđāļāđāļāļŠāļģāļŦāļĢāļąāļāļāļēāļĢāđāļāđāļēāļāļģāļŠāļąāļāļāļēāđāļĨāļ°āļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļāļēāļĄāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļ āđāļāļāļĢāļāļĩāļāļĩāđāļāđāļēāļāđāļĄāđāđāļŦāđāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļāļēāļĢāđāļāđāļāļĢāļ§āļāļĢāļ§āļĄ āđāļāđ āļŦāļĢāļ·āļāđāļāļīāļāđāļāļĒāļāđāļāļĄāļđāļĨāļŠāđāļ§āļāļāļļāļāļāļĨāđāļāļĩāđāļĒāļ§āļāļąāļāļāļĢāļ°āļ§āļąāļāļīāļāļēāļāļāļēāļāļĢāļĢāļĄ āļŦāļĢāļ·āļāļĄāļĩāļāļēāļĢāļāļāļāļāļ§āļēāļĄāļĒāļīāļāļĒāļāļĄāđāļāļ āļēāļĒāļŦāļĨāļąāļ āļāļāļēāļāļēāļĢāļāļēāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāļīāļāļāļēāļĢāđāļāļ·āđāļāļāļĢāļĢāļĨāļļāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāļāļąāļāļāļĨāđāļēāļ§āļāđāļēāļāļāđāļāđāļāđ āđāļĨāļ°āļāļēāļ āļāļģāđāļŦāđāļāđāļēāļāļŠāļđāļāđāļŠāļĩāļĒāđāļāļāļēāļŠāđāļāļāļēāļĢāđāļāđāļĢāļąāļāļāļēāļĢāļāļīāļāļēāļĢāļāļēāļĢāļąāļāđāļāđāļēāļāļģāļāļēāļāļāļąāļāļāļāļēāļāļēāļĢ .
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Help collect and summarize data analysis requirements for data application projects
- Collaborate with Data Product/Data Engineers on metrics framework design, metrics definition clarification, ready-to-use data tables
- Request and to develop fundamental data layer and dashboards for new business projects/initiatives.
- Design market/business insights report and performance measurement dashboards to share with senior management
- Design metrics frameworks to track business/project performance in a structured and systematic way, to reflect business performance and identify any business issue and challenges.
- Initiate ad-hoc analysis to address specific business performance and issues, and produce analysis report to senior
- management/business stakeholders
- Work closely with business stakeholders to understand business operation and performance, and provided valuable and/or actionable insights to support business for decision making/strategy planning.
- Bachelor's degree or equivalent practical experience.
- 6 - 9 years of working experience in an analytical position (business intelligence, MIS or analytics)
- Willingness to learn and use new business intelligence tools (i.e. Alibaba s platforms)
- Familiarity with Data tools and languages, with SQL and Excel are required
- Experience in conducting business analysis, reporting, data analysis, and providing thoughts and insight.
- Experience in business, strategy and/or consulting would be an advantage
- Can-do attitude, proactiveness and resilience to changes.
- Ability to prioritize multiple tasks and navigate independently in ambiguity.
- Solid analytical skills. Ability to analyze campaign performance to derive recommendation.
āļāļąāļāļĐāļ°:
Automation, Big Data, Accounting
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Oversee a Master Data specialist team that analyze and enrich master data elements and optimize the flow data between users and BUs.
- Serve as subject matter expert on Master Data Management for IT and Analytics initiatives.
- Be a Head of master data manages data governance and ensures data integrity by leading data management efforts across the company.
- Collaborate with IT to launch scalable and reliable data solutions, support system integration efforts, and create operational efficiencies through automation and process improvements.
- Oversee initiatives for improving data management process.
- Mentor and coach team members on data management methodologies.
- Evaluate the performance of data systems and seek ways to enhance them.
- Troubleshoot and authorize the maintenance of data-related problems.
- Support team members in their day-to-day duties.
- BS degree in any fields.
- Proven working experience as Big Data Analytics.
- Proven knowledge of Data analytics and Report.
- Advanced computer skills on MS Office, accounting software and databases.
- Ability to manipulate large amounts of data.
- Ability to direct and supervise.
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŋ110,000 - āļŋ130,000, āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- āđāļāđāļāļāļģāļāļĩāļĄāđāļāļāļēāļĢāļāļāļāđāļāļāđāļĨāļ°āļāļąāļāļāļēāđāļāļĨāļđāļāļąāđāļāļāđāļēāļ IT āļāļĩāđāļāļāļāđāļāļāļĒāđāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāļāļāļāļĨāļđāļāļāđāļē.
- āļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāđāļāļĢāļāļāļēāļĢāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļāļąāļāļāļēāļĢāļāļģāđāļŠāļāļāđāļĨāļ°āļāļīāļāļāļąāđāļāđāļāļĨāļđāļāļąāļāđāļŦāđāđāļāđāļāđāļāļāļēāļĄāđāļāđāļēāļŦāļĄāļēāļĒ.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāļĩāļĄāļāļēāļāļāđāļēāļāđ āļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ āđāļāļ·āđāļāđāļŦāđāļāļēāļĢāļāļąāļāļāļēāđāļĨāļ°āļāļīāļāļāļąāđāļāđāļāļĨāļđāļāļąāļāđāļāđāļāđāļāļāļĒāđāļēāļāļĢāļēāļāļĢāļ·āđāļ.
- āļŠāļĢāđāļēāļāļāļ§āļēāļĄāļŠāļąāļĄāļāļąāļāļāđāļāļĩāđāļāļĩāļāļąāļāļĨāļđāļāļāđāļēāđāļĨāļ°āļĢāļąāļāļĐāļēāļāļ§āļēāļĄāļāļķāļāļāļāđāļ.
- āļāļģāļāļĩāļĄāļāļāļāđāļāļāđāļĨāļ°āļāļąāļāļāļēāđāļāļĨāļđāļāļąāđāļ:āļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāļāļāļāļĨāļđāļāļāđāļēāđāļĨāļ°āļĢāļ°āļāļļāļāļąāļāļŦāļēāļāļĩāđāļāđāļāļāļāļēāļĢāđāļāđāđāļ.
- āļāļģāļāļĩāļĄāđāļāļāļēāļĢāļāļāļāđāļāļāđāļĨāļ°āļāļąāļāļāļēāđāļāļĨāļđāļāļąāđāļāļāļĩāđāđāļŦāļĄāļēāļ°āļŠāļĄ.
- āļāļĢāļ°āđāļĄāļīāļāļāļ§āļēāļĄāđāļāđāļāđāļāđāļāđāļāļēāļāđāļāļāļāļīāļāđāļĨāļ°āļāļāļāļĢāļ°āļĄāļēāļāļāļāļāđāļāļĨāļđāļāļąāļ.
- āļāļąāļāļāļģāđāļāļāļŠāļēāļĢāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļāļąāļāđāļāļĨāļđāļāļąāđāļ āđāļāđāļ āļāđāļāđāļŠāļāļāļāļēāļāđāļāļāļāļīāļ (Technical Proposal), āđāļāļāļāļģāļĨāļāļ (Blueprint) āđāļĨāļ°āđāļāļāļāļēāļĢāļāļīāļāļāļąāđāļ.
- āļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāđāļāļĢāļāļāļēāļĢ:āļ§āļēāļāđāļāļāđāļĨāļ°āļāļąāļāļŠāļĢāļĢāļāļĢāļąāļāļĒāļēāļāļĢāļŠāļģāļŦāļĢāļąāļāđāļāļĢāļāļāļēāļĢ.
- āļāļģāļŦāļāļāļāļēāļĢāļēāļāđāļ§āļĨāļēāđāļĨāļ°āļāļīāļāļāļēāļĄāļāļ§āļēāļĄāļāļ·āļāļŦāļāđāļēāļāļāļāđāļāļĢāļāļāļēāļĢ.
- āļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāļāļ§āļēāļĄāđāļŠāļĩāđāļĒāļāđāļĨāļ°āđāļāđāđāļāļāļąāļāļŦāļēāļāļĩāđāđāļāļīāļāļāļķāđāļāļĢāļ°āļŦāļ§āđāļēāļāļāļēāļĢāļāļģāđāļāļīāļāđāļāļĢāļāļāļēāļĢ.
- āļŠāļ·āđāļāļŠāļēāļĢāļāļ§āļēāļĄāļāļ·āļāļŦāļāđāļēāļāļāļāđāļāļĢāļāļāļēāļĢāđāļŦāđāļāļđāđāļĄāļĩāļŠāđāļ§āļāđāļāđāļŠāđāļ§āļāđāļŠāļĩāļĒāđāļāđāļĢāļąāļāļāļĢāļēāļ.
- āļāļĢāļ°āđāļĄāļīāļāļāļĨāđāļĨāļ°āļŠāļĢāļļāļāļāļĨāļāļēāļĢāļāļģāđāļāļīāļāļāļēāļāļāļāļāđāļāļĢāļāļāļēāļĢ.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāļĩāļĄāļāļēāļāļāđāļēāļāđ:āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāļĩāļĄāļāļēāļĒāđāļāļ·āđāļāļāļģāđāļŠāļāļāđāļāļĨāļđāļāļąāđāļāđāļŦāđāļāļąāļāļĨāļđāļāļāđāļē.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāļĩāļĄāļāļąāļāļāļēāđāļāļ·āđāļāļāļąāļāļāļēāđāļĨāļ°āļāļĢāļąāļāļāļĢāļļāļāđāļāļĨāļđāļāļąāđāļ.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāļĩāļĄāļāļīāļāļāļąāđāļāđāļāļ·āđāļāļāļīāļāļāļąāđāļāđāļĨāļ°āļāļāļŠāļāļāđāļāļĨāļđāļāļąāđāļ.
- āļāļĢāļ°āļŠāļēāļāļāļēāļāļāļąāļāļāļĩāļĄāļŠāļāļąāļāļŠāļāļļāļāđāļāļ·āđāļāđāļŦāđāļāļĢāļīāļāļēāļĢāļŦāļĨāļąāļāļāļēāļĢāļāļēāļĒ.
- āļŠāļĢāđāļēāļāļāļ§āļēāļĄāļŠāļąāļĄāļāļąāļāļāđāļāļąāļāļĨāļđāļāļāđāļē:āļŠāļĢāđāļēāļāļāļ§āļēāļĄāļŠāļąāļĄāļāļąāļāļāđāļāļĩāđāļāļĩāļāļąāļāļĨāļđāļāļāđāļēāđāļĨāļ°āđāļāđāļēāđāļāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāļāļāļāļĨāļđāļāļāđāļē.
- āđāļŦāđāļāļģāļāļĢāļķāļāļĐāļēāđāļĨāļ°āļāļģāđāļāļ°āļāļģāļāļēāļāđāļāļāļāļīāļāđāļāđāļĨāļđāļāļāđāļē.
- āļāļģāđāļŠāļāļāđāļāļĨāļđāļāļąāđāļāđāļĨāļ°āļŠāļēāļāļīāļāļāļĨāļīāļāļ āļąāļāļāđāđāļŦāđāļāļąāļāļĨāļđāļāļāđāļē.
- āļāļīāļāļāļēāļĄāđāļĨāļ°āļāļĢāļ°āđāļĄāļīāļāļāļ§āļēāļĄāļāļķāļāļāļāđāļāļāļāļāļĨāļđāļāļāđāļē.
- āļāļĢāļīāļāļāļēāļāļĢāļĩāļŦāļĢāļ·āļāļŠāļđāļāļāļ§āđāļēāđāļāļŠāļēāļāļēāļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļāļāļĄāļāļīāļ§āđāļāļāļĢāđ āļ§āļīāļāļĒāļēāļāļēāļĢāļāļāļĄāļāļīāļ§āđāļāļāļĢāđ āļŦāļĢāļ·āļāļŠāļēāļāļēāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļ.
- āļĄāļĩāļāļĢāļ°āļŠāļāļāļēāļĢāļāđāđāļāļāļēāļĢāļāļāļāđāļāļāđāļĨāļ°āļāļąāļāļāļēāđāļāļĨāļđāļāļąāļāļāđāļēāļ IT āļāļĒāđāļēāļāļāđāļāļĒ 5 āļāļĩ āđāļĨāļ°āļĄāļĩāļāļēāļĢāļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāđāļāļĢāļāļāļēāļĢ IT āļāļĒāđāļēāļāļāđāļāļĒ 3 āļāļĩ.
- āļāļąāļāļĐāļ°āļāļēāļāđāļāļāļāļīāļ:āļĄāļĩāļāļ§āļēāļĄāļĢāļđāđāļāļ§āļēāļĄāđāļāđāļēāđāļāđāļāđāļāļāđāļāđāļĨāļĒāļĩāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļāļąāļāđāļāļĨāļđāļāļąāļāļāļĩāđāļāļģāđāļŠāļāļ.
- āļŠāļēāļĄāļēāļĢāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļĨāļ°āļāļāļāđāļāļāđāļāļĨāļđāļāļąāļāļāļĩāđāļāļāļāđāļāļāļĒāđāļāļ§āļēāļĄāļāđāļāļāļāļēāļĢāļāļāļāļĨāļđāļāļāđāļē.
- āļŠāļēāļĄāļēāļĢāļāđāļāđāđāļāļĢāļ·āđāļāļāļĄāļ·āļāđāļĨāļ°āđāļāļāļāļīāļāļāļĩāđāđāļāļĩāđāļĒāļ§āļāđāļāļāļāļąāļāļāļēāļĢāļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāđāļāļĢāļāļāļēāļĢ.
- āļāļąāļāļĐāļ°āļāđāļēāļāļāļēāļĢāļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢ:āļĄāļĩāļāļąāļāļĐāļ°āđāļāļāļēāļĢāļ§āļēāļāđāļāļāđāļĨāļ°āļāļĢāļīāļŦāļēāļĢāļāļąāļāļāļēāļĢāđāļāļĢāļāļāļēāļĢ.
- āļĄāļĩāļāļąāļāļĐāļ°āđāļāļāļēāļĢāļŠāļ·āđāļāļŠāļēāļĢāđāļĨāļ°āļāļēāļĢāđāļāļĢāļāļēāļāđāļāļĢāļāļ.
- āļĄāļĩāļāļąāļāļĐāļ°āđāļāļāļēāļĢāđāļāđāđāļāļāļąāļāļŦāļēāđāļĨāļ°āļāļēāļĢāļāļąāļāļŠāļīāļāđāļ.
- āļĄāļĩāļāļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļāđāļāļāļēāļĢāļāļģāļāļēāļāđāļāđāļāļāļĩāļĄ.
- āļāļąāļāļĐāļ°āļāļ·āđāļāđ:āļĄāļĩāļāļ§āļēāļĄāļāļĢāļ°āļāļ·āļāļĢāļ·āļāļĢāđāļāđāļĨāļ°āļĄāļĩāļāļ§āļēāļĄāļĢāļąāļāļāļīāļāļāļāļāļŠāļđāļ.
- āļŠāļēāļĄāļēāļĢāļāļāļģāļāļēāļāļ āļēāļĒāđāļāđāđāļĢāļāļāļāļāļąāļāđāļāđāļāļĩ.
- āļĄāļĩāļāļąāļĻāļāļāļāļīāđāļāļīāļāļāļ§āļāđāļĨāļ°āļĄāļĩāđāļāļĢāļąāļāļāļĢāļīāļāļēāļĢ.
āļāļąāļāļĐāļ°:
Procurement, Contracts, Market Research, English
āļāļĢāļ°āđāļ āļāļāļēāļ:
āļāļēāļāļāļĢāļ°āļāļģ
āđāļāļīāļāđāļāļ·āļāļ:
āļŠāļēāļĄāļēāļĢāļāļāđāļāļĢāļāļāđāļāđ
- Manage the full lifecycle of sourcing and procurement for IT requirements, including hardware, software, services, and IT Outsource Turnkey solutions.
- Identify, evaluate, and onboard new potential suppliers to meet organizational needs.
- Negotiate contracts, pricing agreements, and terms with suppliers, ensuring favorable and sustainable conditions.
- Monitor supplier performance and ensure adherence to contractual obligations, addressing any discrepancies as they arise.
- Collaborate with internal stakeholders to understand their requirements and ensure alignment with procurement strategies.
- Proactively identify and resolve procurement-related challenges to avoid operational disruptions.
- Conduct market research and competitor analysis to identify cost-effective, high-quality suppliers that meet the company's needs.
- Educational Background: Bachelor's degree in Supply Chain Management, Business Administration, Information Technology, or a related field. A master's degree or relevant certifications are a plus..
- Experience: Proven experience in IT procurement, sourcing, or vendor management, ideally within a technology-driven environment..
- Technical Knowledge: Strong understanding of IT hardware, software, services, and outsourcing models..
- Negotiation Skills: Demonstrated ability to negotiate contracts and pricing agreements that deliver favorable outcomes for the organization..
- Supplier Management: Experience in identifying, qualifying, and nurturing long-term relationships with suppliers..
- Problem-Solving Abilities: A proactive approach to resolving procurement challenges and driving solutions that support organizational objectives..
- Market Awareness: Ability to conduct comprehensive market research and competitor analysis to identify high-quality, cost-effective suppliers..
- English Communication Skills: Strong verbal and written communication skills in English..