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
