Databricks Data Engineer: Cloud Lakehouse & Pipelines

Ingrity Pty; Sydney; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work environment

Job summary

Ingrity Pty is seeking an experienced Data Engineer to work in a major financial services data modernisation program. The role focuses on Databricks-based data engineering, building and optimising pipelines and supporting cloud migration.

You will work with Python/PySpark, SQL and dbt in a modern lakehouse environment, collaborating across engineers, analysts and business stakeholders to deliver scalable data solutions.

Qualifications

• Experience building data pipelines in Databricks environments.
• Strong PySpark and SQL development skills in a data engineering role.
• Familiarity with dbt, Delta Lake and lakehouse architecture.
• Proven ETL/ELT pipeline development experience.
• Experience with cloud platforms such as Azure or AWS.
• Knowledge of data quality checks, testing and production support.

Responsibilities

• Design, develop and optimise data pipelines using Databricks, Python/PySpark and SQL.
• Build and maintain data transformations using dbt and Delta Lake.
• Develop scalable data models across Bronze, Silver and Gold layers.
• Support data migration from legacy platforms, including SAS.
• Implement data quality checks, testing and performance optimisation.
• Collaborate with data engineers, analysts and business stakeholders.

Skills

Databricks

PySpark

SQL

dbt

Delta Lake

Lakehouse

ETL/ELT

Cloud (Azure/AWS)

Data quality

CI/CD

Collaboration

Tools

Databricks

PySpark

SQL

dbt

Delta Lake

Azure

AWS

Job description

Ingrity Pty is seeking an experienced Data Engineer to work in a major financial services data modernisation program. The role focuses on Databricks-based data engineering, building and optimising pipelines and supporting cloud migration.

You will work with Python/PySpark, SQL and dbt in a modern lakehouse environment, collaborating across engineers, analysts and business stakeholders to deliver scalable data solutions.