Hybrid Data Engineer - Snowflake/Databricks/dbt

NTT DATA Deutschland; Western Australia; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

In-office 4 days/week

Job summary

NTT Data Deutschland is seeking an experienced Data Engineer to join a high-performing team delivering modern data and analytics solutions in a cloud-based environment. The role involves building scalable data platforms using Snowflake, Databricks and dbt, supporting forecasting, analytics and business decision making.

You will design data models, build ETL/ELT pipelines, and implement data quality and governance practices in a hybrid work setting.

Qualifications

• 5+ years of Data Engineering experience.
• Strong experience with Snowflake and data warehousing, including SQL optimisation.
• Hands-on experience with dbt and data modelling.
• Experience building Databricks solutions, including Workflows and CLI.
• ETL/ELT pipeline development and data quality processes.
• Knowledge of Git, CI/CD and deployment automation.
• Strong stakeholder engagement and analytical skills.

Responsibilities

• Design, develop, and maintain scalable data models and dbt transformations.
• Build and optimise datasets through complex transformations, joins, and aggregations.
• Develop SQL-based solutions within Snowflake for performance and reliability.
• Create and maintain Databricks notebooks, workflows, and data pipelines.
• Prepare trusted datasets for forecasting, analytics, and reporting.
• Collaborate with data scientists, analysts and business stakeholders.

Skills

Snowflake

Databricks

dbt

SQL optimization

ETL/ELT Pipelines

CI/CD

Git

Data quality

Tools

Databricks CLI

Databricks Workflows

Job description

NTT Data Deutschland is seeking an experienced Data Engineer to join a high-performing team delivering modern data and analytics solutions in a cloud-based environment. The role involves building scalable data platforms using Snowflake, Databricks and dbt, supporting forecasting, analytics and business decision making.

You will design data models, build ETL/ELT pipelines, and implement data quality and governance practices in a hybrid work setting.