Senior Data Engineer - Java, Spark, Kafka, Spring Boot, and DevOps

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Job Overview

The Applications Development Senior Manager is a senior management level position responsible for accomplishing results through the management of a team or department in an effort to establish and implement new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to drive applications systems analysis and programming activities.

Responsibilities:

• Design, develop, and maintain data processing pipelines using Java, Spark, and Kafka.
• Develop and deploy microservices using Spring Boot.
• Write efficient and scalable code to process large datasets.
• Implement real-time data ingestion and processing solutions using Kafka.
• Optimize Spark applications for performance and scalability.
• Collaborate with analysts, and other engineers to understand data requirements and deliver solutions.
• Develop and maintain unit and integration tests.
• Participate in code reviews and contribute to improving code quality.
• Troubleshoot and resolve production issues.
• Stay up-to-date with the latest technologies and trends in data engineering and microservices.
• Contribute to the design and architecture of our data platform and microservices ecosystem.
• Automate data quality checks and monitoring.
• Implement and maintain API gateways and service discovery mechanisms.
• Ensure the security and scalability of microservices.
• Implement and maintain CI/CD pipelines using tools like Jenkins, GitLab CI, or CircleCI.
• Manage infrastructure as code using tools like Terraform or CloudFormation.
• Monitor application performance and infrastructure using tools like Prometheus, Grafana, or ELK stack.

Qualifications:

• Bachelor's degree in computer science or a related field.
• 8+ years of experience in software development with a focus on data engineering and microservices.
• 5+ years of experience with Java and Spark.
• 5+ years of experience with Spring Boot for building microservices.
• Strong understanding of data processing concepts and techniques.
• Experience with Kafka for real-time data ingestion and processing.
• Proficiency in SQL and experience with relational databases.
• Experience with cloud platforms such as AWS, Azure, or GCP is a plus.
• Familiarity with data warehousing concepts and technologies.
• Experience with big data technologies such as Hadoop, Hive, or Impala is a plus.
• Experience with containerization technologies like Docker and orchestration platforms like Kubernetes.
• Excellent problem-solving and communication skills.
• Ability to work independently and as part of a team.
• Understanding of microservices architecture principles and design patterns.
• Experience with DevOps practices and tools.

Bonus Points:

• Experience with streaming technologies such as Apache Flink or Apache Storm.
• Experience with NoSQL databases such as Couchbase or MongoDB.
• Experience with data visualization tools such as Tableau or Qlik.
• Contributions to open-source projects.
• Experience with security best practices for cloud environments.
• Certifications in cloud platforms or DevOps tools.