Develop and maintain data ingestion and transformation processes in the Data Lake, following the established layered architecture.
Integrate data from different corporate sources, ensuring quality and consistency.
Create and maintain queries, analytical views and exports that feed the company's dashboards and reports.
Support system migrations, with a focus on data sanitization and validation.
Collaborate on adopting artificial intelligence solutions for analysis and report generation.
Monitor processing routines, identify failures and propose continuous improvements.

Experience with AWS data services, especially S3, Glue and Athena, and, as complementary services, CloudFront and Cognito.
Proficiency in SQL for analytical queries and handling large volumes of data.
Experience with Python, preferably with PySpark, for developing ETL routines.
Knowledge of Data Lake architecture and the concept of data layers such as bronze, silver and gold.
Familiarity with integrating data from ERPs and CRMs, with emphasis on SAP and Salesforce.
Familiarity with data modeling and best practices for data quality and governance.
Preferred: experience with ERP migration projects, especially SAP, including data sanitization and migration.
Preferred: experience applying artificial intelligence or LLMs for analysis and report generation.
Analytical reasoning and a focus on practical problem solving.
Organized, detail-oriented and disciplined in validating data prior to delivery.
Good communication skills and the ability to work collaboratively with business teams.
Autonomous and eager to learn, staying up to date with developments in the data market.

Mid/Senior Data Analyst

Key skills