The Moodys Analytics Data Engineer will be responsible for supporting the development of integration point from source systems into the Moodys Analytics platform.
The resource should be able to support data analysts and data scientists on relevant data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
They must be self directed and comfortable supporting the data needs of multiple teams, systems and products.
Work closely with Implementation Managers and analysts to ensure smooth delivery and operation of Acumen data analytics platform.
ETL development (Python)
Test Integrations with source systems and Validate Data
Troubleshoot errors and discrepancies
Produce internal and customer friendly documentation
Must have Moodys Analytics experience
Strong expertise in SQL, including complex selection queries, stored procedures, and performance tuning
Understanding of common data exchange formats such as XML, JSON, and web services
Experience with common ETL, including combining multiple data sources, master data management, and managing data quality
Knowledge of transactional and dimensional data models
Familiarity with business intelligence tools such as Microsoft Power BI or Tableau.
Ability to perform data profiling on diverse source systems