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.
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📌 Data Engineer (New South Wales)
🏢 CareCone Group
📍 New South Wales