Lead Assistant Manager

Data Engineering SQL Data Warehousing Concepts ETL/ELT Development Data Validation and Reconciliation Data Pipeline Development Cloud Technologies Google Cloud Platform (GCP) BigQuery Cloud Storage Cloud Composer (Airflow) Development Tools DBT (Data Build Tool) Git/GitHub Python (Basic to Intermediate) SAS Knowledge Understanding of SAS datasets PROC SQL SAS ETL concepts SAS code analysis Data Modeling Understanding Star Schema Dimension and Fact Tables Source-to-Target Mapping Data Lineage Concepts SAS Migration Support Analyze SAS programs, PROC SQL code, and SAS datasets. Assist in converting SAS transformation logic into DBT models and SQL transformations. Support migration of data from legacy SAS environments to GCP. Participate in code conversion, testing, and reconciliation activities. Data Pipeline Development Develop and maintain ELT pipelines using DBT and BigQuery. Build reusable transformation models following DBT best practices. Implement data ingestion and processing workflows. Support batch and incremental data processing requirements. Data Transformation & Modeling Develop SQL-based transformations for Bronze, Silver, and Gold layers. Implement business rules and data quality validations. Support dimensional models, fact tables, and dimension tables. Assist Data Modelers and Architects in implementing target-state data models. Data Quality & Testing Perform source-to-target validation and reconciliation. Support automated testing using DBT tests. Investigate and resolve data quality issues. Ensure completeness, accuracy, and consistency of migrated data. GCP Development Work with GCP services including: BigQuery Cloud Storage Dataproc Cloud Composer (Airflow) Graduate in Computer Science, Data Science, or related field. 3-4 years of experience in data engineering or a related field.