Senior/Lead Java Developer

1 week ago


Anywhere in IndiaMultiple Locations MindBrain Full time

Job Title :

Senior Lead Java Developer - Spark, Azure, Redpanda Expert.

Experience Level :

Senior/Lead (13+ years of experience).

Job Description :

We are seeking a highly skilled Senior Lead Java Developer with expertise in Apache Spark, Azure Data Services (ADLS, Azure Blob Storage, Azure Databases), and Redpanda.

In this role, you will design, architect, and lead the development of scalable data processing pipelines, leveraging Java and Spark to process vast datasets.

As a senior technical leader, you will collaborate with cross-functional teams to deliver robust, data-driven solutions while establishing best practices in cloud-based architecture and data engineering.

If you are passionate about distributed systems, real-time data processing, and cloud technologies, this role is for you.

Key Responsibilities :

Design and Architect Distributed Data Processing Systems :

- Lead the design and development of large-scale Apache Spark jobs using Java to process massive datasets, including blockchain and financial transactions.

- Architect high-performance, scalable data pipelines integrated with Azure Data Lake Storage (ADLS), Azure Blob Storage, and Azure Databases for both batch and real-time processing.

Development and Optimization of Spark Jobs :

- Build and optimize Spark jobs in Java, ensuring high scalability, fault tolerance, and efficient memory usage.

- Implement data validation, schema management, and handle Parquet files for seamless integration with ADLS and Iceberg tables.

Integration with Redpanda :

- Lead the integration of Redpanda (or similar message brokers like Kafka) for real-time data ingestion, ensuring low-latency communication between ingestion services and downstream processing components.

- Develop efficient Redpanda consumers and integrate them with Spark for real-time streaming data processing.

Azure Cloud Services :

- Design cloud-native solutions utilizing Azure services such as ADLS, Azure Blob Storage, and Azure SQL/NoSQL Databases.

- Collaborate with DevOps teams for seamless integration with Azure services, focusing on data ingestion, storage management, and cost optimization.

- Optimize the storage of large datasets for performance and cost-efficiency.

Lead and Mentor Engineering Teams :

- Provide technical leadership, mentoring, and guidance to developers in Java, Spark, and cloud-native architecture best practices.

- Conduct code reviews, performance tuning, and architecture assessments to maintain code quality and adherence to industry standards.

End-to-End Data Pipeline Management :

- Manage data pipelines from ingestion (via Redpanda) to transformation, storage, and serving using Spark and Azure services.

- Implement monitoring and observability tools such as Prometheus, Grafana, and Azure Monitor to ensure high availability and security.

Performance Tuning and Resource Optimization :

- Optimize Spark jobs for performance and resource utilization, focusing on task scheduling, caching, partitioning, and reducing shuffling.

- Develop strategies to maximize throughput and minimize processing time for large-scale data processing.

Required Qualifications :

- 13+ years of experience in software development with strong expertise in Java and JVM-based technologies.

- 5+ years of hands-on experience with Apache Spark for data processing in Java.

- Proficiency with Azure Data Services (ADLS, Azure Blob Storage, Azure Databases).

- Deep understanding of distributed data processing and integration with streaming frameworks like Redpanda or Kafka.

- Proven experience in designing cloud-native solutions with a focus on Azure.

- Strong expertise in storage optimization, partitioning, and Spark performance tuning.

- Experience with CI/CD pipelines, containerization (Docker, Kubernetes), and DevOps practices.

- Leadership experience with a demonstrated ability to mentor and guide engineering teams.

- Strong knowledge of security best practices for cloud-based data pipelines.

Preferred Qualifications :

- Hands-on experience with Iceberg tables and Parquet file formats.

- Knowledge of monitoring tools like Prometheus, Grafana, or Azure Monitor.

- Experience with streaming data integration using Redpanda and Spark.

- Familiarity with microservices architecture using Spring Boot and cloud-based deployment strategies.

(ref:hirist.tech)
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