Backend Engineer (Java + Big data) - Trading Insights

As a Backend Engineer (Java + Big Data) at Binance, your main duties will revolve around designing and developing microservices architecture using Java Spring Boot, implementing various components such as service discovery and load balancing, analyzing data with big data technologies, and collaborating with business teams to ensure data solutions align with their objectives.

To qualify for the Backend Engineer (Java + Big Data) position at Binance, you should hold a Bachelor's or Master’s degree in Computer Science or a related field. You will need a minimum of 8 years of Java development experience, particularly 3 years focused on Spring Boot microservices, along with expertise in big data technologies and an understanding of cloud services.

At Binance, we provide a dynamic work environment that encourages personal and professional growth. As a Backend Engineer, you'll have opportunities to tackle innovative projects, collaborate with talented individuals, and continuously learn, all of which contribute significantly to your career development.

As a Backend Engineer (Java + Big Data) at Binance, you will be using a variety of tools and technologies including Java Spring Boot, Spring Cloud, big data technologies like Hive, Spark, and Flink, as well as components such as Kafka and Prometheus for performance monitoring and management of large-scale databases.

The work environment for a Backend Engineer at Binance is fast-paced and innovative, with a flat organizational structure that fosters collaboration and autonomy. You’ll be able to work on challenging projects while enjoying flexibility in your work schedule, including potential work-from-home arrangements.

When designing microservices architecture, I start by understanding the business requirements and identify individual services that can be decoupled from each other. I prioritize scalability, reliability, and ease of deployment, and leverage frameworks like Spring Boot to streamline service development.

Spring Cloud provides built-in tools that simplify many tasks associated with microservices management, such as service discovery, configuration management, and load balancing. This allows you to focus on writing business logic while ensuring scalability and resilience.

I've worked with technologies like Apache Hive and Apache Spark for data processing. I typically implement them by leveraging their capabilities for querying large datasets and by utilizing Spark's in-memory processing for high-speed computation.

To ensure performance and optimization, I regularly monitor key metrics and logs, analyze bottlenecks, and apply profiling tools to identify inefficiencies. I also implement caching strategies and optimize database queries to further enhance performance.

I have extensive experience with CI/CD pipelines using tools like Jenkins and GitLab CI. I typically set up automated testing and deployment processes to streamline the release cycle and maintain code quality, ensuring that new features are delivered with reliability.

Handling communication with cross-functional teams involves regular updates, status meetings, and collaboration tools. I prioritize transparency and actively seek feedback to ensure everyone is aligned on project objectives and timelines.

Common challenges include managing data integrity, ensuring high availability, and optimizing query performance across distributed systems. I address these challenges by implementing best practices for database design and indexing strategies.

I have worked with cloud services, particularly AWS, for deploying applications and managing infrastructures. Utilizing services like EC2 for computing and S3 for storage has enhanced my ability to scale applications efficiently.

My troubleshooting strategies involve systematically reproducing issues, analyzing logs, and employing monitoring tools to identify the root cause of problems. I also engage in regular code reviews and cross-team discussions to foresee potential issues.

One complex project involved migrating an existing application to a microservices-based architecture. My role was to design the microservices, coordinate with teams for data migration, and ensure smooth integration with legacy systems, which required both technical skills and effective communication.