Job Description: 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
Responsibilities: 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)
Qualifications: Graduate in Computer Science, Data Science, or related field. 2-3 years of experience in data engineering or related field.