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Key skills for this role
About the Role
Role Summary We are seeking a highly skilled Senior Data Engineer to support the migration of SAS-based data platforms, ETL processes, reporting datasets, and analytical workloads to Google Cloud Platform (GCP) using DBT. The role involves designing, developing, optimizing, and supporting cloud-native data pipelines while ensuring data quality, scalability, security, and compliance. The ideal candidate should possess strong expertise in SQL, Python, PySpark, DBT, BigQuery, and data warehousing concepts, with experience in large-scale data migration and modernization initiatives.
Key Skills for This Role
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Responsibilities
- 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.
- 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.
Qualifications
- Graduate in Computer Science, Data Science, or related field. 4-6 years of experience in data engineering or related field.
About EXL
EXL is a global data and AI company that provides analytics, digital operations, and industry-specific services to enterprises in insurance, healthcare, banking, retail, media, and energy.
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