I will build web scraping, etl and API data pipelines with validation
Full Stack, Backend and Data Engineer
Über diesen Service
Turn scattered website and API data into a repeatable pipeline your team can use.
I build Python collectors and ETL workflows that extract, normalize and validate data for reporting, research and business operations. Delivered client projects include marketplace data collection and API-based data validation.
Every package includes reusable source code, a sample CSV or JSON export, agreed validation checks, and setup/handoff notes. Standard adds cross-source normalization and deduplication. Premium adds scheduling, retries, run logs and one database or API destination.
The packages cover defined sources, fields and an initial validation batch. A source means one website layout or one API workflow; field limits apply to the combined output schema. I review a sample before we agree on scope and acceptance criteria.
Send the source, desired output and update frequency before ordering. Larger collections, additional sources, complex access requirements and ongoing maintenance can be quoted as a custom project. Hosting and third-party fees are separate.
Zielplattform:
PostgreSQL
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Andere
Tools und Plattformen:
Andere
Mein Portfolio
FAQ
What counts as one source?
One website with a consistent page layout, or one defined API workflow. Additional layouts or workflows count separately. Field limits cover the combined output schema.
What will I receive?
Reusable source code, a sample CSV or JSON export, validation results and setup notes. Premium also includes scheduling, retries, logs and one agreed database or API destination.
Can this run regularly or process larger volumes?
Yes. Premium includes a scheduled workflow in one agreed environment. Packages include the stated initial test batch; larger volumes, hosting and ongoing maintenance are scoped separately.
What should we confirm before ordering?
Source access, sample records, desired fields and acceptance criteria. I work with public or authorized data. Revisions refine agreed functionality; new sources or features require additional scope.

