Streaming Data Engineer

As a Streaming Data Engineer, you will be entrusted with the design, development, and implementation of data streaming solutions that cater to both batch and real-time data processing requirements. You will be responsible for building and optimizing scalable data pipelines and architectures, ensuring data is accessible, consistent, and reliable across various platforms. This role demands a keen understanding of distributed computing, stream processing frameworks like Apache Kafka, Apache Flink, or Spark Streaming, and expertise in programming languages such as Java, Scala, or Python. Additionally, you will work on integrating data from diverse sources, including APIs, databases, and event streams, while ensuring data security and compliance with regulatory standards.

Your responsibilities will also encompass monitoring and maintaining the health of the data streaming infrastructure, identifying bottlenecks, and enhancing system performance to ensure low latency and high throughput. Collaborating closely with cross-functional teams such as data scientists, software engineers, and business analysts, you will support the development of real-time analytics and machine learning models, contributing to actionable business insights. You will also be involved in continuous process improvements, adopting industry best practices, and staying abreast of the latest advancements in streaming technologies. Ensuring data integrity, troubleshooting issues, and providing timely resolutions are key aspects of this role, driving the organization's overall data strategy and capabilities.

For a Streaming Data Engineer, degrees in computer science, information technology, or a related field are highly recommended. Certifications such as the Google Cloud Professional Data Engineer, AWS Certified Big Data – Specialty, and Cloudera Certified Professional Data Engineer can be advantageous. Proficiency in stream processing frameworks like Apache Kafka, Apache Flink, or Spark Streaming, as well as experience with programming languages such as Java, Scala, or Python, are critical. Additionally, knowledge of database management and data warehousing solutions, data integration tools, and adherence to data security protocols are essential for this role.