Top Data Engineer Jobs in Osaka

The Data Engineer II will enhance existing business analytics solutions, perform data mining to support sales and market growth, ensure data quality and integrity, analyze datasets for trends, and collaborate across teams for performance forecasting and reporting.

Collaborate with analysis and development teams on data modelling activities, contribute to data application projects, possess expertise in data warehousing and big data technologies, and demonstrate strong communication skills.

The Principal Data Engineer will guide the technical planning and development of critical sales tools and business workflows, focusing on data analysis for decision-making. Responsibilities include managing ETL data pipelines, leading the design and implementation of data products, mentoring engineers, and improving data engineering practices while collaborating with various stakeholders.

Responsible for data business development, data governance, and data platform maintenance in a top cryptocurrency exchange. Requires expertise in Python, big data platforms, SQL, and database management. Strong communication and problem-solving skills.

The Sr Cloud Data Engineer will lead data integration efforts, create and maintain data management standards, develop data pipelines using AWS services, manage complex data models, and present data insights to both technical and non-technical stakeholders. They will ensure data quality and facilitate collaboration among various departments.

The Senior Data Engineer will shape data strategies, address data warehousing challenges, lead design reviews, and mentor junior engineers. Responsibilities include architecting scalable systems and automating cloud infrastructure in a data-driven atmosphere within Autodesk's Customer Success Organization.

The Senior Data Engineer will enhance data processing and analytics pipelines, focusing on scalability, reliability, and business insights. Responsibilities include automating cloud services, developing CI/CD pipelines, and collaborating with stakeholders for analytical needs and product metrics.