About Position:

We are seeking a highly skilled Spark Data Engineer with strong hands-on experience in building scalable data processing solutions using Apache Spark. The ideal candidate should have experience in Java/Scala development, data engineering best practices, and CI/CD implementation for data platforms.
- Role: Data Engineer
- Location: All Persistent Locations
- Experience: 7 to 13 Years
- Job Type: Full time Employment

What You'll Do:
- Design, develop, and optimize large-scale data processing pipelines using Apache Spark.
- Build and maintain batch and real-time data ingestion and transformation workflows.
- Develop scalable data solutions using Java and/or Scala.
- Analyze and improve Spark job performance, resource utilization, and execution efficiency.
- Collaborate with data architects, business analysts, and cross-functional teams to understand requirements and deliver data solutions.
- Implement coding standards, unit testing, and best practices for data engineering projects.




- Build and maintain CI/CD pipelines for automated deployment and testing of data applications.
- Troubleshoot production issues and provide timely resolution.
- Participate in code reviews and ensure high-quality, maintainable code.
- Support cloud-based and distributed data processing environments.

Expertise You'll Bring:
- Apache Spark (Core, Spark SQL, Data Frames, Performance Tuning)
- Java (Intermediate to Advanced)
- Scala (Basic to Intermediate)
- CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, Azure DevOps, etc.
- Git version control
- Experience with Hadoop ecosystem (HDFS, Hive, YARN).
- Experience working on data migration or modernization projects.
- Knowledge of cloud platforms such as AWS, Azure, or GCP.
- Understanding of data warehousing and ETL/ELT concepts.
- Strong problem-solving and analytical skills.
- Look for candidates who can demonstrate:
- Hands-on Spark development experience (not just listed as a skill).
- Performance tuning and optimi

📌 Spark Data Engineer (Pune)
🏢 Persistent
📍 Pune