Data Engineer

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.

• 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.

• 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.