Data Engineer - Big Data

Job Responsibilities :

This role is responsible for designing, building, and maintaining scalable, high-volume data processing systems that support Razer’s internal analytics and AI use cases. The Data Engineer enables the reliable collection, transformation, and storage of raw data into high-quality, trusted datasets for data scientists, business analysts, and downstream applications.

The role focuses on developing and operating data pipelines, data platforms, and integration frameworks to ensure data reliability, performance, and scalability. Working closely with data scientists, analytics engineers, data analysts, data product managers, and other internal stakeholders, the Data Engineer helps unlock insights, power analytics, and enable the effective use of AI and machine learning capabilities across the organization.

Essential Duties and Responsibilities

Design, develop and maintain scalable data systems that enable the organization to store, process, and analyze large volumes of structured and unstructured data used for analytics and AI use cases.

Build and operate reliable data pipelines and platform that support batch and streaming workloads, ensure data freshness, accuracy, and completeness.

Manage data lakes and data warehouses by populating and operationalizing them. This involves designing and creating data-marts, tokenization and vectorization techniques to support Gen AI use cases.

Leverage modern build tools and AI to enhance automation, data quality, testing, and deployment of data pipelines.

Design and implement cloud-based data infrastructure in alignment with the company’s security, governance, and cost optimization policies.

Collaborate with data scientists, data analysts, analytics engineers, data product managers and business users to understand data requirements and translate them into scalable, maintainable data solutions.

Mentor interns for the duration of their internship to upgrade, maintain and implement data pipelines.

Education & Experience

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related discipline.

Minimum of 2 years of hands-on experience in data engineering or a closely related role; supporting, building and improving production data pipelines and platforms.

Pre-Requisites : Skills required

Proven experience in building and maintaining ELT / ETL pipelines using Python, SQL with software programming best practices.

Excellent with various data processing techniques (streaming, batch, event-based), managing and optimizing data storage (Data Lake, Data Warehouse, Vector Data Stores and Database, SQL, and NoSQL).

Hands-on experience with cloud-based data platforms such as AWS (eg. Redshift, Sagemaker, Glue), Snowflake, Google BigQuery, or Azure Data Lake.

Experience using pipeline orchestration tools like Airflow, distributed computing framework like Spark or Dask, data transformation tool like Data Build Tool (DBT).

Proficiency with version control systems (Git) and CI / CD pipelines (Bitbucket pipelines) for data engineering workflows.

Experience using IAC tools such as Terraform, containerization tools like Docker, container orchestration platforms like Kubernetes.

Experience with BI and analytics tools like Superset, PowerBI.

A fast learner who is interested in integrating AI into data engineering, good team player with excellent written and verbal communication skills.

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?