Join Deloitte's Strategy, Risk & Transaction team as an Assistant Manager in Risk Tech. This role focuses on mitigating risk and uncovering opportunities through innovative solutions. You will be part of a dynamic environment that addresses everything from strategic risks to cyber threats, contributing to a team that enhances value for our clients.

This position offers a chance to work with cutting-edge technologies in a collaborative setting. You'll leverage your expertise to build robust data processing systems and contribute to the firm's reputation for excellence in risk management and financial advisory services.

Design, develop, and optimize large-scale data pipelines utilizing PySpark. Build and maintain ETL/ELT workflows for processing diverse data types. Work with big data technologies including Hadoop, Spark, and Impala. Collaborate effectively with data scientists, analysts, and product teams. Ensure high code quality through rigorous reviews and adherence to best practices. Optimize Spark job performance, memory usage, and execution times. Engage in data modeling, transformation, and pipeline orchestration activities. Participate in the full SDLC, from requirement analysis to deployment and troubleshooting. Contribute to the enhancement of automation, monitoring, and logging frameworks.

Demonstrated strong hands-on experience with Python and PySpark is essential. Proficiency in SQL, including advanced querying and performance tuning, is required. Experience with distributed data systems like Hadoop and the Spark ecosystem is necessary. Familiarity with relational databases such as SQL Server, Impala, or Hive is expected. A solid understanding of data structures, algorithms, and performance optimization techniques is crucial. Experience in ETL pipeline development and data warehousing concepts is required. Knowledge of SDLC methodologies, particularly Agile/Scrum, is preferred. Familiarity with version control systems like Git is a must. Proven experience working with large datasets in production environments is necessary. Experience with cloud platforms (Azure, AWS, GCP) and workflow orchestration tools (Airflow, Oozie) is advantageous. A Bachelor's degree in any specialization is required, with 4-8 years of relevant PySpark development experience. Strong analytical, problem-solving, and communication skills are vital.