
Data Enginer
Department:Design
Type:REMOTE
Region:Australia
Location:Australia
Experience:Entry level
Estimated Salary:A$80,000 - A$120,000
Skills:
PYTHONJAVASCALASQLSPARKHADOOPAWSAZUREGCPAIRFLOWKAFKADBTETLELTDATA PIPELINESDATA WAREHOUSINGDATA MODELINGDATA ARCHITECTURECI/CDDEVOPSREAL-TIME DATA STREAMINGDATA LAKELAKEHOUSE
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Job Description
Posted on: March 22, 2026
Data Engineer π¦πΊπ
π Location: Australia π
πΌ Employment Type: Full-time / Part-time β°
About the Role πβ¨
We are seeking a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data pipelines and infrastructure π§©. You will play a critical role in enabling data-driven decision-making by ensuring reliable, high-quality data across the organization ππ‘.
Key Responsibilities π οΈπ
- Design, develop, and maintain scalable data pipelines ππ
- Build and optimize data architectures and data models ποΈπ
- Integrate data from multiple sources (APIs, databases, cloud platforms) ππ
- Ensure data quality, integrity, and security ππ
- Collaborate with data analysts, scientists, and stakeholders π€π¨βπ»
- Monitor and troubleshoot data workflows and performance issues β‘π
- Implement ETL/ELT processes and automation tools π οΈβ±οΈ
- Maintain documentation and data governance standards ππ
Required Skills & Experience π―π‘
- Degree in Computer Science, Data Engineering, or related field π
- Experience in data engineering or similar role π₯οΈ
- Strong programming skills (Python, Java, or Scala) π§βπ»
- Experience with SQL and database systems ποΈ
- Familiarity with big data tools (e.g., Spark, Hadoop) βοΈ
- Knowledge of cloud platforms (AWS, Azure, or GCP) βοΈ
- Understanding of data warehousing concepts π’π
- Strong analytical and problem-solving skills π§ π§
Preferred Qualifications βπ₯
- Experience with tools like Airflow, Kafka, or dbt ππ‘
- Knowledge of CI/CD and DevOps practices βοΈπ
- Experience with real-time data streaming π‘β‘
- Familiarity with data lake and lakehouse architectures πποΈ
What We Offer ππ
- Competitive salary and benefits π°
- Career growth and learning opportunities ππ
- Innovative and data-driven environment π§ β¨
- Flexible working arrangements π‘πΌ
Originally posted on LinkedIn
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