Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.
REQUIREMENTS:
Bachelor’s degree in Data Science, Computer Science, Information Systems, or related field.
Minimum 3 years of experience in data analysis and business intelligence.
Strong proficiency in Power BI (DAX, Power Query) and data modeling.
Proficient in Python for data manipulation and report generation.
Experience with SQL for working with relational databases.
Experience with Agile Tools (JIRA, Confluence, BitBucket, Github)
Excellent problem-solving skills.
Strong communication skills and ability to work cross-functionally.
Experience in handling financial datasets is a strong advantage.
Team player with a proactive and accountable work attitude.
Nice to Have
Experience in fintech, e-commerce, or digital payments industries.
Familiarity with AWS services (e.g., S3, Lambda, Glue).
Experience with cloud data platforms (AWS, GCP, or Azure).
JOB DESCRIPTION:
Design, develop, verify, and deliver ad-hoc or automated operational and financial reports with high accuracy and timeliness.
Build and maintain dashboards using Power BI to support business decision-making.
Analyze data to identify trends, patterns, and insights that can drive business decisions.
Support the development of predictive data models using Python.
Write and optimize SQL scripts for data extraction and manipulation.
Document data processes and create knowledge base documentation.
Collaborate with stakeholders to gather requirements, estimate effort, and implement data solutions across systems.
Develop, enhance, and maintain ETL processes and datasets.
Ensure data quality through validation, cleansing, reconciliation, and troubleshooting.
Work closely with software developers to document data models and manage data dictionaries.
Identify and implement opportunities to improve data tools and reporting processes.
Collaborate with data engineers to ensure data quality and system performance.
Support junior analysts and promote knowledge sharing within the team.
Are you game?
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