Seeking a number of Pyspark Developers with experience in big data processing, Python, and Apache Spark, particularly within the finance domain. Candidates should have experience working with financial instruments, market risk, and large-scale distributed computing systems.
This role involves developing and optimizing data pipelines for risk calculations, trade analytics, and regulatory reporting.
Key responsibilities
1. Develop and optimize scalable PySpark-based data pipelines for processing and analyzing large-scale financial data.
2. Design and implement distributed computing solutions for risk modeling, pricing, and regulatory compliance.
3. Ensure efficient data storage and retrieval using Big Data technologies.
4. Implement best practices for Spark performance tuning including partitioning, caching, and memory management.
5. Maintain high code quality through testing, CI/CD pipelines, and version control (Git, Jenkins).
6. Work on batch processing frameworks for Market risk analytics.
Qualifications and Skills
1. Experience in PySpark and Big Data frameworks.
2. Proficiency in Python and PySpark with knowledge of core Spark concepts (RDDs, DataFrames, Spark Streaming, etc.).
3. Experience working in financial markets, risk management, and financial instruments.
4. Familiarity with market risk concepts including VaR, Greeks, scenario analysis, and stress testing.
5. Hands-on experience with Hadoop and Spark.
6. Proficiency in Git, Jenkins, and CI/CD pipelines.
7. Excellent problem-solving skills and strong mathematical and analytical mindset.
8. Ability to work in a fast-paced financial environment.
Job Family Group: Technology
Job Family: Applications Development
Time Type: Full time
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