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EXL
Data Engineer

GCP Data Engineer

On-siteMidData Engineerposted 1mo ago
✦Role summaryAI-generated

This role focuses on migrating and modernizing legacy SAS data pipelines to GCP using BigQuery, Dataproc, and Airflow, while designing and optimizing data warehouses and pipelines. Candidates will leverage DBT, PySpark, and Python to build ELT workflows and ensure data validation and reconciliation across the organization.

Skills required

About this role

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

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.

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.

Qualifications

Graduate in Computer Science, Data Science, or related field. 4-6 years of experience in data engineering or related field.

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