Citi—Java Spark developer

Job description

Description: 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. 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