Data Engineer

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

• Hybrid work environment - 4 days per week in office
• Work across Databricks, Snowflake, Python and dbt

NTT Data are seeking an experienced Data Engineer to join a high-performing team delivering modern data and analytics solutions in a cloud based environment.

• Contract through to end of June 2027

This is an exciting opportunity to work across Snowflake, Databricks and dbt, helping to build scalable data platforms that support forecasting, analytics and business decision making.

Key Responsibilities

• Design, develop and maintain scalable data models and transformation pipelines using dbt
• Build and optimise high-quality datasets through complex transformations, joins and aggregations
• Develop and support SQL-based solutions within Snowflake, ensuring performance, reliability and scalability
• Build, maintain and deploy Databricks notebooks, workflows and automated data pipelines
• Prepare and manage trusted datasets that support forecasting, analytics and reporting initiatives
• Collaborate closely with data scientists, analysts and business stakeholders to deliver data requirements
• Implement data quality, testing, documentation and governance best practices
• Write clean, maintainable and well-documented code and contribute to code reviews and technical design discussions
• Support CI/CD processes, deployment automation and modern software engineering practices
• Continuously improve platform performance, reliability and data engineering capability

Skills & Experience

• 5+ years' experience in Data Engineering
• Strong experience with Snowflake, data warehousing and SQL optimisation
• Hands-on experience with dbt, including data modelling, testing and documentation
• Experience developing solutions within Databricks, including Workflows, Databricks CLI and Databricks Asset Bundles
• Experience building ETL/ELT pipelines and managing data quality processes
• Knowledge of Git, CI/CD and deployment automation practices
• Strong analytical, problem-solving and stakeholder engagement skills
• Ability to work effectively with complex business and data requirements
• Strong attention to detail and an ownership mindset

Nice to Have

• Experience supporting forecasting, analytics or data science workloads
• Knowledge of time-series data and forecasting concepts
• Experience working with R
• Exposure to modern cloud data platforms and data architectures