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.