Java + PySpark Engineer

Job Title: Java + PySpark Engineer Employment Type: Full-time Work Mode: Onsite Location: Pune, Bangalore, Chennai We are hiring for one of the world's leading professional services firms and a member of the globally recognized Big Four accounting organizations. Key Responsibilities Data Engineering & Development Design, develop, and maintain scalable data pipelines using PySpark and Apache Spark. Build high-performance backend services and microservices using Java, Spring, and Spring Boot. Process and analyze large-scale datasets in distributed computing environments. Develop and optimize ETL/ELT pipelines for data ingestion, transformation, and storage. Integrate data from multiple sources, including databases, APIs, and streaming platforms. Write clean, reusable, and maintainable code following engineering best practices. Perform performance tuning and optimization of Spark jobs and Java applications. Ensure data quality, security, governance, and compliance standards are met. Troubleshoot production issues and provide timely resolutions. Collaboration & Delivery Work closely with data scientists, analysts, architects, and cross-functional teams. Participate in Agile/Scrum ceremonies and contribute to project planning and delivery. Collaborate with stakeholders to understand business requirements and translate them into technical solutions. Required Skills Core Technologies Java (8+) with strong Object-Oriented Programming (OOP) concepts PySpark and Apache Spark (Core, SQL, DataFrames, Streaming) Python for data processing and scripting Backend & Frameworks Spring Framework and Spring Boot REST API Development Microservices Architecture Hibernate / JPA Databases PostgreSQL, MySQL, Oracle, or other relational databases NoSQL databases such as MongoDB, Cassandra, or DynamoDB Strong SQL and database optimization skills Preferred Skills Experience with cloud platforms such as AWS, Azure, or GCP Knowledge of data lake and big data ecosystems Familiarity with CI/CD pipelines, Docker, and DevOps practices Experience working with enterprise-scale data platforms and distributed systems