JobHabor
Location
Bengaluru, Karnataka, India
Workplace
Hybrid
Employment
Full Time
Salary
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Posted today

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. 2-3 years of experience in data engineering or related field.

Skills

  • Attention To Consistency
  • Data Privacy Management
  • Data Quality
  • Data Quality Metrics
  • Database Management and Administration
  • Governance Tools
  • Internal Communications
  • Interpersonal Relationship Building
  • Leadership Capabilities
  • Working under Pressure

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