Why This Role Stands Out
This role offers an exciting opportunity to leverage your extensive dbt, SQL, and Python expertise to build robust data transformation pipelines and scalable data models within a reputable global software services company. You'll thrive here if you're a mid-senior data engineer eager to contribute to diverse client projects across Australia's leading industries. Apply now to advance your career in a dynamic and growth-oriented environment.
Quick Overview
Job Description
XPT Software Australia Pty Ltd Contract
Sydney , Melbourne , Brisbane, Australia Posted on 10/06/2026
- XPT SoftwareAustralia PTY Ltd, incorporated in 2016, is a Software Services company
- XPT works with topclients across Australia in Banking, Insurance, Telecom,Retail, Energy, Mining and Manufacturingdomains.
- We have 120+technocrats in Australia working at our clientlocations.
- XPT SoftwareAustralia is part of group companies which has globalpresence across India & Europe.
- We have served100+ clients globally, fulfilling their onsite-offshoreneeds.
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.
- 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.
- 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
- Snowflake
- Strong understanding of data integration and transformation concepts
- Experience with Python for data engineering/automation
- 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
Data Transformation: dbt, dbt Cloud, dbt Core
Database/Warehouse: Snowflake, Databricks, Redshift, BigQuery
Languages: SQL, Python
ETL/ELT: dbt, Airflow, Fivetran, Matillion
Data Modeling: Star Schema, Snowflake Schema, Dimensional Modeling
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