Data Engineer – Databricks, Lakehouse & ETL (Hybrid)

Cpb; Sydney; Hybrid; AUD 120,000 - 180,000; Full time

Benefits offered by this job

Monthly Lifestyle Allowance

Novated Leasing

Loyalty Leave

Inclusive Parental Leave Policy

Work From Anywhere

Job summary

INGRITY is seeking an experienced Data Engineer to join a major financial services organisation undergoing a significant data modernisation program. You’ll work in a modern Databricks environment, building scalable data pipelines and transforming complex datasets, supporting migration of legacy data platforms to a cloud-based lakehouse architecture.

You will collaborate with data engineers, analysts and stakeholders, ensuring data quality, testing and performance optimisation within a hybrid

Qualifications

• Strong hands‑on experience with Databricks, PySpark and SQL.
• Experience with dbt, Delta Lake and lake house 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.

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 pipelines

Azure or AWS

insurance / financial services

GitHub Copilot or Databricks Genie

Tools

Python

Job description

INGRITY is seeking an experienced Data Engineer to join a major financial services organisation undergoing a significant data modernisation program. You’ll work in a modern Databricks environment, building scalable data pipelines and transforming complex datasets, supporting migration of legacy data platforms to a cloud-based lakehouse architecture.

You will collaborate with data engineers, analysts and stakeholders, ensuring data quality, testing and performance optimisation within a hybrid