Associate Data Engineer
Razer is hiring an Associate Data Engineer in Singapore, Singapore. Level rates it ; you can apply on Razer.
Level's read on this job
- Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Python, Spark and Airflow.
- Level classifies it as a junior role.
- Level lists 149 other open roles at Razer.
- The role was posted in the last few days.
AI in this role
Build and maintain big data processing systems and pipelines to support data science, analytics, and AI applications.
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 :
This role is required to build and maintain high volume big data processing systems that enable the organization to collect, manage, and convert raw data into usable information for data scientists and business analysts, and enabling the use of Artificial Intelligence (AI) capabilities. He / She is responsible for developing and maintaining data pipelines, data storage systems, and cloud infrastructure, while working closely with data scientists, data analysts and internal stakeholders to utilize data for analytics and AI capabilities.Essential Duties and Responsibilities
- Develop and maintain data systems and data pipelines that enable the organization to store, process, and analyze large volumes of data. This involves developing data pipelines, implementing data storage systems, and ensuring that data is integrated effectively to support Analytics and AI applications.
- Manage data lakes and data warehouses by populating and operationalizing them. This involves creating and managing table schemas, views, materialized views, including tokenization and vectorization techniques for Gen AI.
- Develop and maintain data pipelines that enable extract, transform, and load operations from various sources. This involves using cloud computing tools to build streaming and batch processing pipelines that handle large volumes of data which can also be used for Analytics and AI applications.
- Monitor and troubleshoot data workflows, ensuring timely resolution of failures and rerunning failed jobs to ensure data completeness and data freshness.
- Leverage modern build tools to enhance automation, data quality, testing, and deployment of data pipelines.
- Develop and implement cloud infrastructure that are in line with company's security policies and practices, as well as cost optimization practices.
- Collaborate with analytics engineers, data engineers, data scientists and business users to understand the data needs of various stakeholders across the organization to implement appropriate solutions.
Requirements
- Bachelor’s or Master’s degree in computer science, engineering, mathematics or similar discipline with 1 year’s experience.
- Ability to write clean, maintainable, scalable and robust code using Python, SQL.
- Experience in building and maintaining ETL/ELT pipelines using Python and optimizing SQL.
- Exposure to cloud data services such as AWS Redshift, Snowflake, BigQuery, or Azure Data Lake.
- Experience using pipeline orchestration tools like Airflow, containerization tools like Dockers.
- Excellent with various data processing techniques (streaming, batch, event-based), optimizing data storage (Data Lake, Data Warehouse, Vector Data Stores and Database, SQL, and NoSQL).
- Experience using data transformation tool like Data Build Tool (DBT).
- Experience with version control (Git) and CI/CD pipelines (Bitbucket pipelines) for data engineering workflows.
- Experience using IAC tools such as Terraform, container orchestration platforms like Kubernetes.
- Excellent problem-solving and analytical skills, with an understanding of AI technologies and their applications.
- Excellent written and verbal communication skills for collaboration across teams.
Pre-Requisites :
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?
How we rate this
Associate Data Engineer at Razer rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $146k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where cloud infrastructure was part of your work. What did you do?
- Tell me about a project where vectorization was part of your work. What did you do?
- Walk me through how you've used Python in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Engineering, ETL, Cloud Infrastructure, Vectorization, and Python. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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