Top Data Jobs in Singapore

The role involves analyzing large data sets, applying statistical techniques, and collaborating with cross-functional teams to drive product strategy and improvements.

Lead the Payments Optimization team at Airwallex, focusing on improving payment success rates through advanced data science techniques like contextual bandits and predictive modeling.

The role focuses on advancing data and AI governance, implementing innovative strategies, maintaining compliance, and integrating governance controls into workflows. Responsibilities include proactive detection systems and collaboration across teams to ensure operational efficiency and audit readiness.

The Strategic Enterprise Account Executive will grow strategic accounts, manage customer relationships, drive sales, and expand Databricks usage across organizations.

Drive revenue growth for the Nielsen/Google partnership, manage sales performance, and collaborate with internal teams to enhance commercial strategies.

Develop next-gen data infrastructure solutions for AI initiatives, collaborating with data teams and ensuring system reliability and compliance.

The Senior Data Engineer will design and implement ETL processes, manage data pipelines, ensure data governance, and leverage AI in data systems while collaborating cross-functionally.

As a Data Engineer II, you'll design data models, manage ETL pipelines, ensure data governance, and explore integrations with AI to enhance data solutions.

The Head of Financial Services APJ GTM Leader will drive Databricks' GTM strategy in Asia Pacific, develop partnerships, advise customers, and lead cross-functional teams.

As a Security Operations Associate, you'll detect and address cybersecurity threats, analyze data, and collaborate to implement security strategies.

The Data Sales Relationship Manager generates new sales within Asia, builds customer relationships, achieves sales targets, and mentors junior employees while analyzing market trends and customer needs.

The Data Production Engineer will automate data tasks, support trading teams, analyze data sets, and ensure data pipeline quality and reliability.

As a Consultant, you'll develop data strategies and optimize data operations for clients in Financial Services or Insurance, overseeing projects and ensuring effective communication with stakeholders.

Wayvia is building a talent pipeline for engineering roles focusing on backend systems, data pipelines, and product engineering. They seek curious and collaborative engineers to connect with and solve future challenges.

Join Data Intellect's Graduate Academy as a developer, receiving training in Q programming and kdb+. Collaborate with leading financial institutions after training.

Lead the development of data analytics initiatives, utilizing AWS data lake to provide insights, establish governance, and mentor teams.

The role involves collecting and analyzing data related to user behavior and product performance, assisting in creating reports and dashboards, and supporting A/B testing efforts.

Assist in data collection, reporting, quality checks, and onboarding for sustainability data. Collaborate with global teams and develop reporting tools.

Lead the implementation of data analytics strategies, managing interdisciplinary teams to deliver data projects, overseeing budgets, and ensuring client engagement.

The Cloudera Data Engineer is responsible for building and managing data pipelines and platforms, focusing on the Cloudera Hadoop ecosystem while collaborating with data teams.

Lead the design and implementation of a secure, scalable cloud data platform on AWS, integrating various tools for data management and analytics while ensuring compliance and security.

The role involves overseeing data center infrastructure, managing teams, optimizing processes, and ensuring operational efficiency in cloud operations.

The Senior Data Scientist will implement machine learning solutions, conduct experiments, communicate findings, and guide junior team members to drive business results.

Lead the migration of data infrastructure to AWS, redesign Python scripts for AWS services, and create documentation and training for users.

Lead the migration of data infrastructure to AWS, re-architect Python scripts and automation workflows, and ensure seamless data operations with zero disruption. Create documentation, conduct training, and validate migrated systems.