Data Engineer ( Fresh Graduate Position )

Gamer2Gamer; Kuala Lumpur; On-site; MYR 60,000 - 120,000; Full time

Job summary

G2G in Malaysia is seeking a Data Engineer to own ETL/ELT pipelines, data modeling, and analytics. You will work with senior engineers on a modern AI-assisted workflow, delivering reliable data for dashboards and business decisions.

The role suits fresh graduates through 3 years of experience, with hands-on SQL, Python, AWS Glue, and Tableau familiarity. You will build data lakes, datamarts, and reports while focusing on data quality and scalable pipelines.

Qualifications

• Bachelor’s degree in Computer Science / Data Engineering or related field.
• 0–3 years of relevant experience; fresh graduates welcome with demonstrable project ownership.
• Proficient in SQL and knowledge of Python; experience with ETL/ELT.
• Solid understanding of data modeling and data warehouse / data lake concepts.
• Strong attention to data quality, analytical and problem-solving skills.

Responsibilities

• Develop, maintain, and optimize ETL/ELT pipelines using AWS Glue and Spark.
• Build ingestion for structured and semi-structured data into the S3 data lake.
• Develop data models and datamarts; maintain source-to-target mappings.
• Implement data validation, monitor pipelines, and respond to incidents.

Skills

SQL

Python

ETL/ELT

Data Modeling

Data Warehousing

Education

Bachelor's degree in CS/DI

Tools

AWS Glue

Tableau

PySpark

Apache Iceberg

Job description

G2G is a global gaming marketplace serving millions of buyers and sellers worldwide. Our Data
team owns the company’s analytics platform end to end — a fully serverless AWS lakehouse
processing billions of records across multiple brands and AWS accounts — and delivers the
pipelines, datamarts, and Tableau dashboards that drive daily business decisions.

We are hiring a Data Engineer whose role spans both data engineering (ETL/ELT, data
modeling, pipeline operations) and data analytics (reporting, dashboards, stakeholder insights).
You will work directly with senior engineers on a modern, AI-assisted engineering workflow, and
see your work used by the business every day. We welcome candidates from fresh graduates
through mid-level (up to 3 years of experience); scope and ownership will be matched to your
level.

Responsibilities

1. Data Engineering

• Develop, maintain, and optimize ETL/ELT pipelines using AWS Glue (Spark), Glue workflows,
  and triggers.
• Build ingestion for structured and semi-structured data from databases (AWS DMS / CDC),
  APIs, and file sources into the S3 data lake.
• Develop data models and curated datamarts in Athena/Iceberg, maintaining source-to-target
  mappings based on business rules.
• Implement data validation and quality checks; monitor production pipelines and respond to
  alerts.
• Investigate and resolve pipeline failures and data quality incidents through structured rootcause
  analysis.
• Optimize SQL queries, Athena scan volumes, and Glue job configurations for performance and
  AWS cost efficiency.

2. Analytics & Reporting

• Build, extend, and maintain Tableau dashboards.
• Translate stakeholder requests into well-defined metrics, datasets, and reports.
• Develop and operate automated reporting so business teams receive accurate, timely data.
• Validate report accuracy and investigate discrepancies raised by business users.

3. Platform & Practices

• Use AI tooling (e.g., Claude, MCP integrations) to accelerate development, operations, and
  reporting workflows.
• Document pipelines, data mappings, processes, and incident resolutions.
• Handle data responsibly: follow PII, security, and access-control practices (IAM, KMS, scoped
  datamarts).
• Contribute to engineering standards, code reviews, and continuous improvement within the
  Data team.

Requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related
  field.
• 0–3 years of relevant experience. Fresh graduates are welcome — demonstrable project
  ownership (academic, personal, or internship) is a must-have.
• Proficiency in SQL and working knowledge of Python (depth expected to match experience
  level).
• Solid understanding of ETL/ELT, data modeling, and data warehouse / data lake concepts.
• Strong attention to data quality, accuracy, and detail.
• Strong analytical and problem-solving skills; able to troubleshoot data workflows to root cause.
• Good communication and documentation skills; able to work with both technical and nontechnical
  stakeholders.
• Willingness to learn AWS cloud data technologies and AI-assisted engineering practices.
• Ability to work independently and take ownership of assigned work, with support scaled to your
  level.

Nice to Have

• Hands-on experience with AWS services such as S3, Glue, Athena, Lambda, or DMS.
• Experience with Apache Spark / PySpark or open table formats (Apache Iceberg, Delta Lake,
  Hudi).
• Experience with BI tools such as Tableau or Power BI.
• Experience using AI coding tools (Claude, Copilot, Codex) or exposure to MCP / LLM
  integrations.
• Exposure to streaming platforms (Kinesis, Kafka) or workflow orchestration tools.
• Understanding of data governance, PII handling, security, and compliance principles.
• Familiarity with Git, CI/CD, or Infrastructure as Code.