What are the responsibilities and job description for the Data Engineer QA position at Recurring Decimal?
Required Skills :
- Strong understanding of data fields, file layouts, and data mappings between systems.
- Experience with data extract comparison techniques, ensuring data consistency and accuracy.
- Experience in supporting data extracts testing, particularly in complex system upgrades (e.g., BMP upgrades).
- Proficient in maintaining and managing change logs, particularly in relation to data extract modifications.
- Expertise in analyzing the downstream impacts of changes to data extracts, including sequence changes, data position changes, data field name changes, and format updates.
- Familiarity with data field characteristics (optional vs mandatory), and the ability to identify and address issues related to changes in these characteristics.
- Knowledge of data validation techniques and tools used in Data Quality Assurance.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication skills to work with both technical and non-technical teams.
Preferred Skills
- Experience with data management or data engineering platforms.
- Knowledge of SQL, data query tools, and data comparison software.
Key Responsibilities:
Data Mapping & File Layouts:
- Develop and maintain an understanding of file layouts, data fields, and data mappings across different systems.
- Act as the primary point of contact for business teams and functions to understand data requirements and translate them accurately.
Data Extract Comparisons:
- Conduct thorough comparisons of data extracts to ensure consistency and accuracy between expected and actual results.
- Identify discrepancies and work with relevant teams to resolve issues efficiently.
Support Upgrade Testing:
- Support Data Extracts testing for the system upgrade by ensuring data quality, validation, and mapping are correctly executed.
- Collaborate with cross-functional teams to ensure smooth execution of upgrade tests.
Change Log Maintenance:
- Maintain an up-to-date log of all changes made to data extracts, ensuring clear documentation of changes to fields, formats, and any system impacts.
- Ensure that all changes are tracked and communicated effectively to the necessary teams.
Impact Analysis:
- Analyze the downstream impacts of changes made to data extracts, ensuring that changes do not negatively affect other systems, processes, or teams.
- Provide insights and recommendations to minimize disruptions and ensure data integrity.
