Contract Data Engineer: Azure Databricks & ETL

Silk Laser; Sydney; On-site; AUD 90,000 - 120,000; Full time

Job summary

MediAesthetics is seeking an experienced Data Engineer on a 3-month contract to strengthen the cloud data platform.

You'll design, build and optimise data pipelines across Azure Databricks and related data ecosystem, delivering scalable solutions for BI, analytics and decision-making. Collaborate with Technology, Analytics and business stakeholders to ensure high-quality, reliable data.

Qualifications

• 4+ years of experience in Data Engineering or similar role.
• Strong SQL with optimisation and complex transformations.
• Python for automation and data processing.
• Experience with Azure, Databricks and cloud data platforms.
• Knowledge of ETL/ELT, data warehousing, and API integrations.
• Experience with Git, source control and CI/CD practices.

Responsibilities

• Design, develop and maintain scalable ETL/ELT pipelines using Azure Databricks.
• Build and support data ingestion processes from internal and external source systems.
• Develop API integrations and automated data pipelines.
• Write and optimise SQL queries for extraction, transformation and validation.
• Build automation and data processing solutions using Python.
• Investigate and resolve data quality, integrity and performance issues.
• Monitor and troubleshoot production data pipelines.
• Collaborate with business and technology stakeholders to deliver data solutions that support reporting and analytics.
• Document data architecture, transformations and data flows.

Skills

SQL

Python

Azure Databricks

Data warehousing

ETL/ELT

API Integrations

Git

CI/CD

Data quality

Tools

Azure

Databricks

Git

Job description

MediAesthetics is seeking an experienced Data Engineer on a 3-month contract to strengthen the cloud data platform.

You'll design, build and optimise data pipelines across Azure Databricks and related data ecosystem, delivering scalable solutions for BI, analytics and decision-making. Collaborate with Technology, Analytics and business stakeholders to ensure high-quality, reliable data.