Big Data Engineer
NXTGIG Sydney
NXT GIG is seeking a proficient Big Data Engineer to join our rapidly growing team. In this pivotal role, you will be responsible for designing, building, and maintaining scalable big data solutions that support our data analytics initiatives.
Your expertise will enable efficient data processing and storage, while leveraging technologies such as Hadoop, Spark, and cloud-based services. You will collaborate closely with data scientists, analysts, and other engineers to ensure data is accessible and ready for analysis.
Your expertise will enable efficient data processing and storage, while leveraging technologies such as Hadoop, Spark, and cloud-based services. You will collaborate closely with data scientists, analysts, and other engineers to ensure data is accessible and ready for analysis.
The ideal candidate will have a strong background in big data technologies, a deep understanding of data architecture, and a passion for transforming raw data into valuable insights. If you are eager to tackle complex data challenges in an innovative environment, we encourage you to apply to NXT GIG.
Responsibilities- Design and implement scalable big data pipelines and architectures to collect, process, and store massive datasets.
- Collaborate with data scientists and analytics teams to understand data requirements and provide optimized access to data.
- Monitor and optimize big data environments for performance, cost-efficiency, and reliability.
- Integrate new data sources and maintain existing data flows to ensure data quality and availability.
- Implement data governance practices to ensure compliance with data management standards.
- Stay updated with emerging big data technologies and best practices, and suggest improvements as necessary.
- Document architecture, processes, and workflows to support knowledge sharing within the team.
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Proven experience as a Big Data Engineer or in a similar role.
- Strong proficiency in big data technologies such as Hadoop, Spark, and NoSQL databases.
- Experience with data processing frameworks and tools, such as Apache Kafka and Hive.
- Familiarity with cloud services (AWS, Azure, or Google Cloud) for big data solutions.
- Understanding of data modeling and ETL processes.
- Strong analytical skills and ability to effectively communicate insights and findings.
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