Mid-Level Data Engineer optimizing data pipelines for tgndata's data platform powering global brands. Responsible for building, refactoring, and ensuring the speed and quality of large-scale datasets.
Responsibilities
Design, build, and optimize data pipelines that collect and transform large-scale product datasets
Work with Python, SQL, and modern orchestration tools to make our data ecosystem more robust and scalable
Refactor and optimize data workflows for speed, quality, and maintainability
Implement monitoring and observability (logging, alerting, data validation) to ensure reliability
Partner with the data engineer and backend teams to ship features that push our services forward
Contribute ideas to improve architecture and guide data best practices
Requirements
3-5+ years of experience in Python for data engineering or ETL development
Strong understanding of SQL, relational data models, and schema design
Experience building or maintaining ETL/ELT pipelines (Airflow, Prefect, dbt, or similar)
Familiarity with cloud environments (AWS, GCP, or Azure)
Analytical mindset - you care about data quality, performance, and scale
Collaborative communicator who enjoys working across teams
Bonus: experience with web scraping, APIs, or data ingestion at scale
Benefits
private health insurance
25 days paid leave + your birthday off
monthly lunch allowance
social team events
support for courses, conferences, and certifications
Job title
Experienced Data Engineer – Python, ETL, Scalable Pipelines
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