- Design, develop, and maintain robust data pipelines to support data ingestion, transformation, and storage.
- Collaborate with cross-functional teams to understand data requirements and deliver high-quality data solutions.
- Implement data models and architectures that support analytics and reporting needs.
- Optimize data processing workflows for performance and scalability.
- Monitor and troubleshoot data pipeline performance and reliability issues.
- Ensure data quality and integrity through rigorous testing and validation processes.
- Document data engineering processes, architectures, and best practices.
- Stay updated with the latest trends and technologies in data engineering and analytics.

Mandatory Skills:

- Robust expertise in data engineering concepts and practices.
- Proficiency in programming languages such as Python, Java, or Scala.




- Experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
- Hands-on experience with ETL tools and frameworks (e.g., Apache Airflow, Talend, Informatica).
- Familiarity with big data technologies (e.g., Hadoop, Spark).
- Solid understanding of SQL and database management systems.
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services.

Preferred Skills:

- Knowledge of data governance and data security best practices.
- Experience with machine learning frameworks and libraries.
- Familiarity with data visualization tools (e.g., Tableau, Power BI).
- Understanding of Agile methodologies and project management practices.

#J-18808-Ljbffr

📌 Data Engineer: Build Scalable Data Pipelines (New South Wales)
🏢 CareCone Group
📍 New South Wales