Data Analyst

Act from raw data through to delivery for analytics, building and maintaining ETL/ELT pipelines with Python and SQL, as well as collecting external data via web scraping when necessary. The focus is on quality, traceability, automation, and compliance, avoiding fragile pipelines.

Responsibilities

• Develop and maintain ETL/ELT pipelines with Python and SQL.
• Process and standardize data, including cleaning, deduplication, validations, business rules, and enrichments.
• Implement web scraping from public sources, with rate limiting, reprocessing, versioning, logging, and handling changes on the website.
• Structure collection routines with fault tolerance, for example retries, backoff, and error capture.
• Create data layers for analytical consumption, with documentation and a data dictionary.
• Monitor pipelines, create alerts, quality metrics, audit, and reconciliation.
• Work with stakeholders to translate business needs into data and technical specifications.
• Ensure good governance practices, privacy, and proper use of data, especially for external sources.

Requirements

• Solid experience with Python for data manipulation, automation, and integration.
• Experience with SQL and transformation routines.
• Experience with data pipelines, ETL/ELT, and publishing to a data warehouse or data lake.
• Practical experience with web scraping, including HTML parsing and pagination mechanisms.
• Knowledge of Git and good development practices, testing, and documentation.