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Posted 06 August, 2026

Data Platform Engineer

vocus
40 Miller St, North Sydney NSW 2060, Australia Full Time
Reference: 487_674165_6262

We are seeking a skilled and proactive Data Engineer to join Vocus Data Platform team and contribute to the development, execution and maintenance of our end-to-end data pipelines.

In this role, you will collaborate with stakeholders and senior team members to implement scalable architectures across AWS and Databricks. You will focus on building robust ETL/ELT process, optimising existing pipelines and ensuring reliable data delivery across the organisation.

Key Responsibilities

  • Designing, building and supporting enterprise-scale data platforms and data integration solutions in Databricks
  • Advanced SQL development skills and strong proficiency in Python, PySpark, and modern data engineering frameworks
  • Designing and implementing reusable, metadata-driven ingestion frameworks, as well as establishing engineering standards, reusable patterns, and platform accelerators
  • Working with cloud-based data platforms including AWS and Databricks, with hands-on experience in technologies such as Redshift, Databricks, Delta Lake, S3, Glue, Lambda, and MWAA
  • Dimensional modelling, data warehousing concepts, and supporting analytical data structures (such as Medallion architecture)
  • Designing and implementing data quality frameworks, automated validation controls, and data observability practice
  • Develop and maintain reliable batch, near real-time, and real-time ingestion pipelines leveraging metadata-driven frameworks in Databricks
  • Manage workflow orchestration using AWS Airflow (MWAA), implement efficient serverless AWS Lambda and Job pipelines in Databricks.

Skills & Experience

  • 5+ years of hands-on Data Engineering (Databricks Preferred)
  • Strong core experience with AWS Services
  • Solid hands-on experience in building job pipelines, streaming, and managing cluster configurations within the Databricks ecosystem
  • Strong production-grade Python and PySpark skills
  • Advanced SQL for complex querying, data manipulation, and expertise in modern data warehouse/lakehouse data modelling techniques
  • Good knowledge and practical experience with CI/CD pipelines and infrastructure-as-code using Terraform.

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