Join a dynamic team focused on mitigating risks and uncovering new value opportunities within financial and regulatory domains. This role is integral to our mission of providing end-to-end risk services, from strategic guidance to addressing complex cyber threats. We are seeking talented professionals to contribute to innovative solutions.

Our Risk, Regulatory & Forensic practice is at the forefront of helping entities navigate complex challenges. This is an opportunity to work with a leading firm and make a significant impact in a critical area of business.

As a key member of the team, you will design, develop, and optimize robust data pipelines, primarily using PySpark. You will build and maintain ETL/ELT workflows, leveraging big data technologies like Hadoop, Spark, and Impala to process diverse datasets.

Key duties include collaborating with cross-functional teams, ensuring code quality through rigorous reviews and best practices, and optimizing Spark job performance. You will also participate in the full SDLC, troubleshoot production issues, and contribute to automation, monitoring, and logging frameworks.

We are looking for candidates with strong hands-on experience in Python and PySpark, alongside advanced SQL skills for querying and performance tuning. Familiarity with distributed systems like Hadoop and Spark ecosystem, as well as experience with Impala, Hive, or SQL Server is essential.

A solid understanding of data structures, algorithms, and performance optimization is required, along with experience in ETL pipeline development and data warehousing concepts. Knowledge of SDLC methodologies and version control systems like Git is also crucial. Experience with cloud platforms (Azure, AWS, GCP) and workflow orchestration tools (Airflow, Oozie) is preferred. A Bachelor's degree in any specialization is required, with 0-2 years of hands-on PySpark developer experience.