Join our Risk Tech team in Pune as a skilled Senior Developer, specializing in PySpark to design, construct, and maintain robust data processing solutions. This role involves comprehensive data engineering stack experience and a solid understanding of distributed computing within an SDLC framework.

We are also seeking an experienced Python Backend Developer adept at building and managing scalable backend systems and APIs, with expertise in Python frameworks, database design, and performance tuning.

Additionally, we need a DevOps Engineer to establish, automate, and preserve highly available, secure, and scalable infrastructure, leveraging cloud platforms and modern DevOps practices.

Key responsibilities include designing, developing, and optimizing large-scale data pipelines using PySpark, and building/maintaining ETL/ELT workflows for diverse data types. You will collaborate with big data technologies like Hadoop, Spark, and Impala, and work closely with cross-functional teams including data scientists and analysts.

Further duties involve ensuring code quality through best practices and code reviews, optimizing Spark job performance and resource management, and contributing to data modeling, transformation, and pipeline orchestration. Participation in end-to-end SDLC activities, troubleshooting production issues, and developing automation, monitoring, and logging frameworks are also crucial.

Essential qualifications include strong proficiency in Python and PySpark, coupled with advanced SQL skills for querying and performance tuning. Experience with distributed data systems like Hadoop and Spark, as well as databases such as Impala, Hive, or SQL Server, is vital.

A deep understanding of data structures, algorithms, and performance optimization techniques is required, alongside experience in ETL pipeline development and data warehousing concepts. Familiarity with SDLC methodologies (Agile/Scrum preferred) and version control systems like Git is necessary.

Preferred candidates will have 1-2 years of hands-on PySpark development experience with real-time project delivery, a Bachelor's degree, and exposure to the full data pipeline lifecycle. Comfort with large-scale data processing and optimization challenges is expected.