About this role
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.