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
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 root-cause analysis.
Optimize SQL queries, Athena scan volumes, and Glue job configurations for performance and AWS cost efficiency.
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.
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 non-technical 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.
Experience in e-commerce, marketplace, or gaming domains.