## Java Spark developerApply: Hybrid: Chennai Tamil Nadu India: Full time: Posted Today: End Date: October 6, 2026 (7 days left to apply): 26987817We are seeking an experienced and motivated **Java Spark Developer** to design, develop, and maintain high-performance, large-scale data processing pipelines and distributed applications. In this role, you will leverage **Core Java** and **Apache Spark** to build resilient batch and real-time streaming data architectures, optimize distributed data workloads, and collaborate with cross-functional teams including Data Scientists, Cloud Engineers, and Solution Architects. ## **1. Data Pipeline & Application Development*** Design, implement, and maintain robust, scalable data ingestion and ETL/ELT pipelines using **Apache Spark (Core, SQL, Streaming)** written in **Java** (or Scala interoperability).* Develop performant, low-latency microservices and distributed processing modules integrated with messaging platforms (e.g., Apache Kafka).* Build and maintain interfaces to relational databases, distributed data lakes, and NoSQL stores (e.g., Hive, Cassandra, HBase, MongoDB, Delta Lake, Snowflake).## **2. Performance Tuning & Optimization*** Profile, debug, and optimize Spark jobs by managing partitioning strategies, caching, broadcast variables, memory allocation (driver/executor memory), and data serialization (Kryo).* Analyze query execution plans, DAGs, and Spark UI metrics to eliminate data skew, reduce shuffle overhead, and minimize bottleneck latencies.* Monitor resource utilization on cluster managers such as Kubernetes, Apache YARN, or cloud-native orchestration engines.## **3. Architecture & Data Modeling*** Design structured, semi-structured, and unstructured data storage schemas using columnar file formats (e.g., Parquet, ORC, Avro).* Implement robust data validation, cleansing, data governance, and error-handling mechanisms across the ingestion lifecycle.* Ensure data privacy and enterprise compliance by applying encryption at rest/transit and access-control policies.## **4. Collaboration, CI/CD & Best Practices*** Participate in Agile/Scrum ceremonies, sprint planning, and code reviews to ensure adherence to high code quality standards.* Write comprehensive unit, integration, and automated regression tests using frameworks such as JUnit, Mockito, and Spark Testing Base.* Configure and maintain continuous integration and continuous deployment (CI/CD) pipelines using tools like Jenkins, GitLab CI, or GitHub Actions.## **Required Qualifications & Skills**## **Technical Competencies*** **Core Java:** Deep proficiency in Java (Java 8/11/17+), including multithreading, concurrency, OOP principles, memory management, and JVM internals.* **Apache Spark:** Hands-on experience developing distributed applications with Apache Spark (RDDs, DataFrames, Datasets, Spark SQL, Spark Structured Streaming).* **Distributed Ecosystem:** Strong working knowledge of distributed architecture (HDFS, YARN), Hive, and distributed storage systems.* **Messaging & Streaming:** Practical experience with event streaming platforms such as **Apache Kafka** or RabbitMQ.* **Database & Query Languages:** Advanced SQL capabilities, experience with relational databases (PostgreSQL, Oracle, MySQL) and NoSQL datastores.* **Build & Version Control:** Proficiency with build tools (Maven, Gradle) and Git version control workflows.* **Testing:** Solid track record in Test-Driven Development (TDD) using JUnit, Mockito, and distributed testing patterns.## **Professional Experience & Education*** **Education:** Bachelor’s or Master’s degree in Computer Science, Information Technology, Software Engineering, or a related technical discipline.* **Experience:** 3-6 years of professional software engineering experience, with at least 2–4 years dedicated to building scalable distributed data processing applications using Java and Apache Spark.## **Preferred / Desired Qualifications*** **Cloud Platforms:** Experience building and deploying data architectures on AWS (EMR, S3, Glue, Athena), Azure (Databricks, HDInsight, ADLS), or Google Cloud (Dataproc, BigQuery).* **Modern Lakehouse Technologies:** Hands-on exposure to Apache Iceberg, Delta Lake, or Apache Hudi.* **Containerization & Orchestration:** Familiarity with Docker, Kubernetes, and workflow schedulers like Apache Airflow or Luigi.* **Polyglot Exposure:** Familiarity with Scala or Python (PySpark) is an added advantage.------------------------------------------------------## **Job Family Group:**Technology------------------------------------------------------## **Job Family:**Applications Development------------------------------------------------------## **Time Type:**Full time------------------------------------------------------## **Most Relevant Skills**Please see the requirements listed above.------------------------------------------------------## **Other Relevant Skills**For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------*Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.*