We 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._ _If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review_ _Accessibility at Citi (https://www.citigroup.com/citi/accessibility/application-accessibility.htm)_ _._ _View Citi's_ _EEO Policy Statement (https://www.citigroup.com/global/eeo-aa-policy)_ _and the_ _Know Your Rights (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)_ _poster._ Citi is an equal chance and affirmative action employer. Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity.

📌 Java Spark developer (Chennai)
🏢 Citigroup
📍 Chennai