Data Engineer

Razer

2-4 Years | Chengdu, Sichuan, China (On Site) | Full Time | 1 day ago

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Job Summary

Join Razer to build and optimize data pipelines and platforms for analytics, product improvements, and AI/ML data needs. Collaborate with cross-functional teams to ensure data reliability, accessibility, and governance. The role involves designing, developing, and maintaining data pipelines, optimizing data warehouse solutions, orchestrating workflows with Airflow, and implementing transformations with DBT. You will also develop Spark jobs for large-scale datasets and apply data quality and compliance practices.

Must Have

Design, develop, and maintain batch and basic real-time data pipelines
Build and optimize data warehouse / data lake solutions
Orchestrate workflows with Airflow; implement transformations and models with DBT
Implement dimensional and ETL data models
Develop Spark jobs for processing large-scale datasets
Apply data quality, lineage, access control, and compliance practices
Strong Python and SQL skills
Hands-on experience with Redshift, Airflow, DBT
Mandatory hands-on experience with Apache Spark
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

Good 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
Exposure to Apache Flink and Apache Kafka
Understanding of Hadoop ecosystem components

Perks & Benefits

Opportunity to make an impact globally
Working across a global team
Gamer-centric #LifeAtRazer experience
Accelerated growth, personally and professionally
Inclusive, respectful, and fair workplace
Reasonable accommodations for disability or religious practices
Certified a Great Place to Work® in US and Singapore
Recognized as a Singapore Top Employer

Job Description

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

14 Skills Required For This Role

Team Management Cross Functional Design Patterns Game Texts Apache Flink Linux Aws Apache Kafka Hadoop Spark Data Science Docker Python Sql