We are seeking a highly skilled and experienced Senior Software Engineer specializing in Java and Apache Spark to join our dynamic team. The ideal candidate will be passionate about building robust, scalable, and high-performance applications, with a strong focus on distributed data processing and big data technologies. You will contribute to all phases of the development lifecycle, driving best practices in software engineering, and be instrumental in designing, developing, and maintaining critical systems that leverage modern Java ecosystems and large-scale data processing frameworks.

Responsibilities

Design, develop, and maintain high-quality, scalable, and efficient Java-based applications, with a significant emphasis on data processing pipelines using Apache Spark.
Contribute to architectural discussions and decisions, ensuring solutions are scalable, maintainable, performant, and aligned with enterprise standards for big data and distributed systems.
Implement and enforce best practices in object-oriented programming, design patterns, and SOLID principles.
Champion Test-Driven Development (TDD) and Domain-Driven Design (DDD) methodologies.
Optimize application performance, considering JVM internals, memory management, garbage collection, and Spark job tuning.
Work with various database technologies, including relational and NoSQL, ensuring data integrity and optimal performance for both operational and analytical workloads.
Leverage cloud-native services and container orchestration platforms (e.g., Kubernetes, OpenShift) for deploying and managing applications and Spark clusters.
Participate in code reviews, providing constructive feedback and ensuring code quality, security, and adherence to coding standards.
Contribute to the continuous improvement of CI/CD pipelines and development tooling for both Java and Spark applications.
Actively engage in documentation of designs, processes, and systems to foster knowledge sharing.

Required Skills And Qualifications

Java & Concurrency

Java Core: Strong proficiency in Java fundamentals, including Equals/hashCode, Collections Framework, Generics, Lambdas, and new features.
Concurrency: Deep understanding and practical experience with Java Concurrency APIs and patterns.
Spring Ecosystem: Extensive experience with Spring Framework (Core, Boot, Data, Security, Batch, Integration, JDBC).
JVM Expertise: Solid understanding of JVM internals, class loading, memory model, garbage collection mechanisms, and performance tuning.

Big Data & Distributed Systems

Apache Spark: Proven expertise with Apache Spark (RDD, Spark SQL, DataFrames, DataSets) for large-scale data processing.
Big Data Ecosystem: Experience with other Big Data technologies such as Hadoop, Hive, Impala, or similar.
Containerization: Hands-on experience with Docker or similar containerization technologies.
Orchestration: Experience with Kubernetes, OpenShift, or similar container orchestration platforms for deploying and managing distributed applications and Spark workloads.

Computer Science Fundamentals

Data Structures: In-depth knowledge of common data structures and their appropriate use, including time/space complexity analysis.
Algorithms: Awareness and application of searching and sorting algorithms, especially in a distributed context.

Databases

Relational Databases: Strong command of SQL, database design, transaction management, and indexing strategies.
NoSQL Databases: Experience with at least one NoSQL database (e.g., MongoDB, Graph DB).

Architecture & Design

Object-Oriented Programming (OOP): Expert-level understanding of OOP principles, design patterns, and SOLID principles.
Domain-Driven Design (DDD): Practical experience with DDD concepts and their application.
Test-Driven Development (TDD): A strong advocate for TDD and experience in writing comprehensive unit, integration, and end-to-end tests for both Java and Spark components.
System Architecture: Demonstrated experience with scalable, transactional, and resilient architectures; familiarity with middleware and messaging systems (e.g., JMS, Solace).

SDLC & Tooling

Version Control: Proficient with Git or similar version control systems.
Build Tools: Experience with Maven, Gradle, or similar build automation tools.
CI/CD: Practical experience with CI/CD tools (e.g., Jenkins) and continuous delivery practices, specifically for Java and Spark applications.
Quality & Security: Familiarity with code quality tools (e.g., SonarQube) and secure coding practices.
Reviews: Proven experience in conducting design and code reviews, focusing on maintainability, performance, and adherence to standards for complex distributed systems.
Documentation: Appreciation for and contribution to comprehensive technical documentation.

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Job Family Group:

Technology

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Job Family:

Applications Development

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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Senior Developer - Java & Spark – Assistant Vice President