Java Engineer (Analytics)

Skills

Bachelor's degree in Computer Science or a related field. 7+ years of experience in software engineering with a focus on streaming data pipelines and analytics. Strong programming skills in Java. Experience with a public cloud provider with a focus on GCP (in Recent project) Strong experience with messaging/stream processing systems such as Google Cloud Pub/Sub and Google Cloud DataFlow. Experience with Apache Beam. Experience with data warehousing and data lake technologies Strong understanding of data modeling data governance and data security Excellent problem-solving skills with the ability to work independently and collaboratively Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders Experience with machine learning and data science technologies is a plus Certification in GCP is required.

Description

We are seeking an experienced Senior Java Engineer, Analytics with a focus on Streaming on GCP cloud to join our team. As a Senior Java Engineer, you will play a key role in designing, building, and maintaining our real-time analytics infrastructure. You will work closely with our data scientists, product managers, and other engineers to develop and deploy scalable, efficient, and reliable data pipelines.

Responsibilities

• Design, build, and maintain large-scale streaming data pipelines using technologies such as Apache Beam, Apache Kafka, Apache Kinesis, Google Cloud Pub/Sub, and Google Cloud Dataflow
• Develop and implement streaming data processing jobs using programming languages like Java.
• Work with data scientists and product managers to develop and deploy real-time analytics applications
• Collaborate with other engineers to integrate streaming data pipelines with our data warehouse and data lake
• Work with public cloud providers such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure
• Monitor and troubleshoot streaming pipelines to ensure high availability and performance.
• Implement DevOps principles and practices to ensure efficient and reliable deployment of batch processing systems
• Knowledge of containerization technologies such as Docker and Kubernetes.