Sr. Data Analyst – ETL, SQL, AWS Glue at Mavensoft Technologies.
Portland, Oregon, United States — full-time
Title: Sr. Data Analyst – ETL, SQL, AWS Glue
Location: Portland, OR – Hybrid – (Mon and Fri can be remote. Tues-Thurs is onsite)
Duration: 8 Months – W2 Role
We are seeking an experienced Sr. Data Analyst – Data Migration, Mapping to support a data modernization project focused on inspection and correction data across multiple source systems, databases, and applications.
Key Responsibilities
Performs detailed analysis of inspection and correction data across multiple source systems, databases and applications to understand how data is structured, stored, maintained and used by the business.
Researches source databases and system tables to identify table names, field names, relationships, data types, key values and data dependencies needed to support data conversion and migration work.
Creates clear source-to-target data mappings that align legacy inspection and correction data to the new data model, schema and ingestion requirements for a modernized database environment.
Works closely with business stakeholders, application teams, database administrators, data engineers and project teams to validate data definitions, resolve mapping questions and ensure data meaning is preserved during conversion.
Identifies data gaps, inconsistencies, duplicates and quality issues that could impact successful ingestion into the new database, and documents recommended remediation steps.
Translates business rules and operational inspection/correction processes into technical data requirements, including mapping logic, transformation rules and validation criteria.
Develops and maintains detailed documentation, including data dictionaries, table inventories, mapping workbooks, schema alignment notes, conversion assumptions and open data issues.
Supports data conversion planning, mock loads, validation activities and issue resolution to help ensure inspection and correction data is accurately prepared for ingestion into the new database.
Acts as a knowledgeable resource for project team members by explaining source-system data structures, data lineage, table relationships and conversion impacts.