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.Job Responsibilities/ 工作职责 :Join Razer to help build and optimize data pipelines and data platforms that support analytics, product improvements, and foundational AI/ML data needs. Collaborate with cross-functional teams to ensure data is reliable, accessible, and governed. Tech stack includes Redshift, Airflow, and DBT.Key ResponsibilitiesDesign, develop, and maintain batch and basic real-time data pipelinesBuild and optimize data warehouse / data lake solutions (Redshift, S3, etc.)Orchestrate workflows with Airflow; implement transformations and models with DBTImplement dimensional and ETL data models with attention to performance and reuseDevelop Spark jobs for processing large-scale datasetsApply data quality, lineage, access control, and compliance practicesSupport analytics, product, and data science with curated, trusted datasets and featuresLeverage Hadoop ecosystem concepts where applicable (e.g., storage, formats, metadata)Optimize ETL processes and recommend improvementsExplore and adopt useful tooling; document workflowsQualificationsBachelor’s degree in Computer Science, Data, or related field2–4 years of data engineering or related experienceStrong Python and SQLHands-on experience with Redshift, Airflow, DBTMandatory hands-on experience with Apache Spark (batch and/or structured processing)Exposure to Apache Flink and Apache Kafka (concepts or basic implementation)Understanding of Hadoop ecosystem components (storage formats, metadata, resource concepts)Familiar with ETL design patterns and performance tuningBasic Linux and Docker knowledgeExperience with at least one cloud platform (AWS preferred)Awareness of data quality and access control practicesSolid problem-solving and cross-team collaboration abilityNice to HaveExperience with feature engineering or early MLOps patternsExperience with data catalog tools (e.g., OpenMetadata)Gaming, e-commerce, or fintech domain exposurePre-Requisites/ 任职要求 :Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.Are you game?
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