Data Engineer - Databricks

Ingrity Pty; Sydney; Híbrido; AUD 120 000 - 180 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work environment

Resumo da oferta

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.

Qualificações

• 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.

Responsabilidades

• 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.

Conhecimentos

Databricks

PySpark

SQL

dbt

Delta Lake

Lakehouse

ETL/ELT

Cloud (Azure/AWS)

Data quality

CI/CD

Collaboration

Ferramentas

Databricks

PySpark

SQL

dbt

Delta Lake

Azure

AWS

Descrição da oferta de emprego

Location: Sydney / Brisbane (Hybrid)
Contract: 12 Months
Industry: Financial Services / Insurance

Data Engineer – Databricks

The Opportunity

INGRITY is seeking an experienced Data Engineer to join a major financial services organisation undergoing a significant data modernisation program.

You'll work within a modern Databricks environment, building scalable data pipelines, transforming complex datasets and supporting the migration of legacy data platforms to a cloud-based lakehouse architecture.

Key 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 & Experience

• Strong hands-on experience with Databricks, PySpark and SQL.
• Experience with dbt, Delta Lake and lakehouse architecture.
• Proven experience developing and maintaining ETL/ELT pipelines.
• Experience with cloud platforms, ideally Azure or AWS.
• Understanding of CI/CD, data testing and production support.
• Experience in insurance or financial services highly regarded.
• Exposure to AI-assisted development tools such as GitHub Copilot or Databricks Genie advantageous.

Why Join?

• Work on a large-scale data transformation program.
• Modern Databricks and cloud technology environment.
• Collaborative engineering team with hybrid flexibility.
• Opportunity to contribute to AI-enabled data engineering practices.