Java Spark developer

• *Discover your future at Citi**
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Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

• *Job Overview**
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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**
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• 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**
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• 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**
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• 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**
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• 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**
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• *Technical Competencies**
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• **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**
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• **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**
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• **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.

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• *Job Family Group:**
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Technology

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• *Job Family:**
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Applications Development

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• *Time Type:**
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Full time

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• *Most Relevant Skills**
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Please see the requirements listed above.

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• *Other Relevant Skills**
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For complementary skills, please see above and/or contact the recruiter.

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• 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.*