Associate Data Engineer

About the role

Razer is hiring an Associate Data Engineer to build and maintain high-volume big data processing systems that turn raw data into usable information for data scientists and business analysts, and to enable the use of artificial intelligence. The role covers data pipelines, data storage systems and cloud infrastructure, working closely with data scientists, data analysts and internal stakeholders.

Key responsibilities

• Develop and maintain data systems and pipelines that store, process and analyze large volumes of data, supporting analytics and AI applications.
• Manage data lakes and data warehouses, including table schemas, views and materialized views, and apply tokenization and vectorization techniques for Gen AI.
• Build streaming and batch processing pipelines using cloud computing tools, covering extract, transform and load operations.
• Monitor and troubleshoot data workflows, rerun failed jobs and ensure data completeness and freshness.
• Use modern build tools to improve automation, data quality, testing and deployment of pipelines.
• Develop cloud infrastructure aligned with security policies, cost optimization and company practices.
• Collaborate with analytics engineers, data engineers, data scientists and business users to meet stakeholder data needs.

Required profile

• Bachelor's or Master's degree in computer science, engineering, mathematics or a similar discipline with 1 year of experience.
• Ability to write clean, maintainable, scalable and robust code.
• Excellent problem-solving and analytical skills, with an understanding of AI technologies and their applications.
• Excellent written and verbal communication skills for cross-team collaboration.

Required skills

• Python and SQL; ETL/ELT pipelines and SQL optimization.
• Cloud data services such as AWS Redshift, Snowflake, BigQuery or Azure Data Lake.
• Pipeline orchestration (Airflow) and containerization (Docker).
• Data processing techniques (streaming, batch, event-based) and storage (data lake, warehouse, vector stores, SQL, NoSQL).
• Data Build Tool (DBT), Git, Bitbucket pipelines, Terraform and Kubernetes.