DBT Data Engineer

XPT Software; Sydney; On-site; AUD 140,000 - 190,000; Full time

Job summary

XPT Software in Sydney seeks an experienced DBT Data Engineer to design and implement scalable data pipelines using dbt. You will build complex SQL models, develop data warehousing solutions, and ensure data quality across cloud platforms.

The role collaborates with data architects, analysts, and BI teams to deliver robust data products. Ideal candidates have 8+ years of data engineering experience, strong Python skills, and familiarity with CI/CD and modern cloud warehouses.

Qualifications

• 8+ years of data engineering experience.
• Hands-on with dbt Core/Cloud and SQL.
• Strong data warehousing and dimensional modeling knowledge.
• Experience building dbt models, macros, snapshots, seeds, tests.
• Knowledge of incremental models and materializations.
• Experience with data quality and testing frameworks.
• Git and CI/CD fluency; cloud data warehouses (Snowflake/Databricks/Redshift/BigQuery) favored.
• ETL/ELT pipeline development and Python scripting.

Responsibilities

• Design, develop, and maintain scalable data transformation pipelines using dbt.
• Develop complex SQL-based data models using dbt.
• Build and maintain staging, intermediate, and mart layers following dbt best practices.
• Implement dbt models, macros, snapshots, seeds, tests, and incremental models.
• Develop reusable SQL transformations for large datasets.
• Implement data quality checks and automated testing using dbt.
• Build data lineage and documentation using dbt documentation.

Skills

dbt

SQL

Python

Data Warehousing

Data Modeling

CI/CD

Cloud Data Platforms

Data Quality

Git

Tools

Git

CI/CD

Snowflake

Databricks

Redshift

BigQuery

Job description

We are seeking an experienced DBT Data Engineer with 8+ years of experience in data engineering, data transformation, and cloud data platforms. The ideal candidate should have strong hands-on expertise in dbt (Data Build Tool), SQL, Python, data warehousing, and cloud data platforms. The role will focus on building scalable transformation pipelines, developing reliable data models, and implementing data quality and testing frameworks.

Job Overview

We are seeking an experienced DBT Data Engineer with 8+ years of experience in data engineering, data transformation, and cloud data platforms. The ideal candidate should have strong hands-on expertise in dbt (Data Build Tool), SQL, Python, data warehousing, and cloud data platforms. The role will focus on building scalable transformation pipelines, developing reliable data models, and implementing data quality and testing frameworks.

Key Responsibilities

• Design, develop, and maintain scalable data transformation pipelines using dbt.
  
• Develop complex SQL-based data models using dbt.
  
• Build and maintain staging, intermediate, and mart layers following dbt best practices.
  
• Implement dbt models, macros, snapshots, seeds, tests, and incremental models.
  
• Develop reusable and optimized SQL transformations for large datasets.
  
• Implement data quality checks and automated testing using dbt.
  
• Build and maintain data lineage and documentation using dbt documentation.
  
• Integrate dbt with cloud data platforms and enterprise data pipelines.
  
• Optimize data models and SQL queries for performance and cost.
  
• Implement incremental loading and Change Data Capture (CDC) strategies where required.
  
• Work closely with Data Architects, Analysts, BI Developers, and Business stakeholders.
  
• Troubleshoot data pipeline and transformation failures in development and production environments.
  
• Implement CI/CD processes for dbt deployments using Git and DevOps tools.
  
• Follow data governance, security, quality, and engineering best practices.
  
• Participate in code reviews, technical design discussions, and Agile ceremonies.
  

Must Have Skills

• 8+ years of overall Data Engineering experience
  
• Strong hands-on experience with dbt / dbt Core / dbt Cloud
  
• Advanced SQL skills
  
• Strong experience in data warehousing and dimensional data modeling
  
• Experience developing dbt models, macros, snapshots, seeds, and tests
  
• Strong understanding of incremental models and materializations
  
• Experience with data quality and testing frameworks
  
• Strong experience with Git and CI/CD
  
• Hands‑on experience with at least one modern cloud data warehouse:
  • Snowflake
    
  • Databricks
    
  • Amazon Redshift
    
  • Google BigQuery
    
• Experience developing ETL/ELT pipelines
  
• Strong understanding of data integration and transformation concepts
  
• Experience with Python for data engineering/automation
  

Nice to Have

• Experience with AWS / Azure / GCP
  
• Experience with Airflow / Dagster / Prefect
  
• Experience with Snowflake
  
• Experience with Databricks / Delta Lake
  
• Experience with Amazon Redshift
  
• Experience with Fivetran / Matillion / Informatica
  
• Experience with Kafka or streaming data
  
• Experience with Terraform
  
• Experience with Docker
  
• Experience with data governance and catalog tools
  
• Experience working in Agile/Scrum environments
  

Technical Skills

Data Transformation: dbt, dbt Cloud, dbt Core

Database/Warehouse: Snowflake, Databricks, Redshift, BigQuery

Languages: SQL, Python

ETL/ELT: dbt, Airflow, Fivetran, Matillion

DevOps: Git, CI/CD, GitHub/GitLab/Azure DevOps

Data Modeling: Star Schema, Snowflake Schema, Dimensional Modeling

Cloud: AWS / Azure / GCP

Data Quality: dbt Tests, Data Validation, Data Reconciliation

Methodology: Agile / Scrum