Data Engineer ( Fresh Graduate Position )

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.