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EXL

GCP Data Engineer

EXL

. Analyze SAS programs, PROC SQL code, and SAS datasets .

Posted 10/7/2026full-timeHyderabad • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Proficient in SQL and data warehousing concepts, with expertise in developing and maintaining ELT pipelines using DBT and BigQuery. Strong understanding of data validation, reconciliation, and migration processes within Google Cloud Platform environments.

Highest-signal resume keywords
SQLDBT (Data Build Tool)Google Cloud Platform (GCP)BigQueryData Warehousing Concepts

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data Pipeline DevelopmentETL/ELT DevelopmentData Validation and ReconciliationSAS Code AnalysisPROC SQLUnderstanding of SAS DatasetsStar SchemaDimension and Fact TablesSource-to-Target MappingData Lineage Concepts
Soft Skills
Strategic GuidanceTeam ManagementContinuous Improvement
Tools & Technologies
Cloud StorageCloud Composer (Airflow)Git/GitHubPython
Certifications & Qualifications
Bachelor's Degree
Industry Keywords
Data EngineeringData QualityData IngestionData Processing WorkflowsAutomated Testing

Tech Stack

Tools & technologies
AirflowBigQueryCloudETLGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact
  • 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
  • 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
  • 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
  • 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
  • Work with GCP services including BigQuery, Cloud Storage, Dataproc, and Cloud Composer (Airflow)
  • Manage data engineering projects
  • Provide strategic guidance
  • Oversee data engineering team
  • Ensure continuous improvement of data processes

Requirements

What you’ll need
  • Bachelor's Degree
  • SQL
  • Data warehousing concepts
  • ETL/ELT development
  • Data validation and reconciliation
  • Data pipeline development
  • Google Cloud Platform (GCP)
  • BigQuery
  • Cloud Storage
  • Cloud Composer (Airflow)
  • DBT (Data Build Tool)
  • Git/GitHub
  • Python (basic to intermediate)
  • Understanding of SAS datasets
  • PROC SQL
  • SAS ETL concepts
  • SAS code analysis
  • Star schema
  • Dimension and fact tables
  • Source-to-target mapping
  • Data lineage concepts