Quick Overview
Seniority
Mid Senior
Employment type
Full Time
Work mode
Hybrid
Location
Sydney, Sydney, Australia
SQLScalaAWSETLApacheAzureConfluenceDatabricksGitHiveJenkinsJiraKafkaPythonStakeholder Management
Job Description
We are hiring a hands-on Data Engineer to design, build, and optimize scalable data pipelines on Azure Databricks. This role is ideal for someone with strong experience in Spark, Scala, SQL, Python, and modern cloud-based data engineering platforms.
Location: Sydney
Key Responsibilities- Design and develop scalable ETL/ELT pipelines using Azure Databricks, Spark/Scala, and SQL.
- Build data solutions following medallion architecture and Delta Lake best practices.
- Develop real-time and near real-time data integrations using Spark Streaming and Kafka.
- Operationalize data workloads through scheduling, CI/CD, Git-based workflows, secrets management, and observability.
- Collaborate with stakeholders to deliver reliable, high-quality data engineering solutions.
- Strong hands-on experience with Azure Databricks.
- Proficiency in Scala Spark, SQL, and Python.
- Experience with data warehousing concepts and big data technologies.
- Exposure to Azure and/or AWS cloud platforms.
- Knowledge of Hive, Impala, Sqoop, Spark Streaming, Apache Kafka, or Confluent Kafka will be advantageous.
- Familiarity with CI/CD tools such as Azure DevOps, GitHub, Jenkins, Jira, or Confluence.
- Strong communication and stakeholder management skills.
If you are passionate about building high-performing data platforms and enjoy solving complex data engineering challenges, we would love to hear from you.
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