GCP Data Engineer

Core Technologies • DBT (Data Build Tool) • Google BigQuery • SQL • Python • PySpark • Git GCP Services • BigQuery • Cloud Storage • Dataproc • Cloud Composer (Airflow) • Dataflow • IAM SAS Technologies • SAS Base • SAS Enterprise Guide • PROC SQL • SAS Macros • SAS Data Sets Data Engineering • ETL / ELT Development • Data Warehousing • Data Pipeline Design • Performance Optimization • Data Validation & Reconciliation Data Modeling • Star Schema • Snowflake Schema • Dimensional Modeling • Source-to-Target Mapping SAS Migration & Modernization • Analyze existing SAS datasets, ETL jobs, PROC SQL code, and SAS macros. • Convert SAS transformation logic into DBT models and cloud-native data pipelines. • Support migration of historical and incremental data from SAS platforms to GCP. • Participate in migration assessments, code conversion, and reconciliation activities. Data Engineering & Development • Design and develop scalable ELT pipelines using DBT and BigQuery. • Build and optimize data ingestion, transformation, and aggregation processes. • Develop reusable and modular DBT models following best practices. • Implement performance tuning for SQL and BigQuery workloads. • Create and maintain data lineage and metadata documentation. Data Quality & Reconciliation • Design and implement data quality validation frameworks. • Perform source-to-target reconciliation between SAS and GCP platforms. • Investigate and resolve data inconsistencies and migration issues. • Support automated testing and monitoring of data pipelines. Cloud Platform Development • Build and manage solutions using: • BigQuery • Cloud Storage • Dataproc • Cloud Composer (Airflow) • Dataflow • Support data security, access controls, and governance requirements. Collaboration & Delivery • Work closely with Data Architects, Business Analysts, Data Modelers, and QA teams. • Participate in design reviews and sprint planning sessions. • Estimate effort and provide technical input during project planning. • Mentor junior engineers and enforce engineering best practices. Graduate in Computer Science, Data Science, or related field. 4-6 years of experience in data engineering or related field.