Manager

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.