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 Responsibilities

Design, develop, and maintain batch and basic real-time data pipelines

Build and optimize data warehouse / data lake solutions (Redshift, S3, etc.)

Orchestrate workflows with Airflow; implement transformations and models with DBT

Implement dimensional and ETL data models with attention to performance and reuse

Develop Spark jobs for processing large-scale datasets

Apply data quality, lineage, access control, and compliance practices

Support analytics, product, and data science with curated, trusted datasets and features

Leverage Hadoop ecosystem concepts where applicable (e.g., storage, formats, metadata)

Optimize ETL processes and recommend improvements

Explore and adopt useful tooling; document workflows

Qualifications

Bachelor’s degree in Computer Science, Data, or related field

2–4 years of data engineering or related experience

Strong Python and SQL

Hands-on experience with Redshift, Airflow, DBT

Mandatory 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 tuning

Basic Linux and Docker knowledge

Experience with at least one cloud platform (AWS preferred)

Awareness of data quality and access control practices

Solid problem-solving and cross-team collaboration ability

Nice to Have

Experience with feature engineering or early MLOps patterns

Experience with data catalog tools (e.g., OpenMetadata)

Gaming, e-commerce, or fintech domain exposure

Pre-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?