RAPS CONSULTING INC
Key Responsibilities
Design and implement scalable data pipelines for market, reference, and transactional data. Develop ETL processes to ingest data from trading platforms, market data providers, and internal systems. Collaborate with trading desks, risk teams, and compliance to understand data requirements. Ensure data integrity, lineage, and governance across systems. Optimize data storage and retrieval for real-time and batch processing. Support regulatory reporting and analytics through reliable data infrastructure. Maintain documentation and contribute to data architecture decisions.
Required Skills
Strong proficiency in Python, SQL, and data modeling. Experience with capital markets data (e.g., equities, fixed income, derivatives). Hands-on experience with cloud platforms (AWS, Azure, or GCP). Knowledge of data governance frameworks and metadata management. Experience with Kafka, Spark, Airflow, or similar tools for data orchestration.
Soft Skills
Strong analytical and problem-solving mindset. Excellent communication with both technical and non-technical stakeholders. Ability to thrive in a fast-paced, high-stakes trading environment.
Qualifications
Bachelor's or Master's degree in Computer Science, Finance, or related field. 5-7 years of experience in data engineering, preferably in financial services.
Design and implement scalable data pipelines for market, reference, and transactional data. Develop ETL processes to ingest data from trading platforms, market data providers, and internal systems. Collaborate with trading desks, risk teams, and compliance to understand data requirements. Ensure data integrity, lineage, and governance across systems. Optimize data storage and retrieval for real-time and batch processing. Support regulatory reporting and analytics through reliable data infrastructure. Maintain documentation and contribute to data architecture decisions.
Required Skills
Strong proficiency in Python, SQL, and data modeling. Experience with capital markets data (e.g., equities, fixed income, derivatives). Hands-on experience with cloud platforms (AWS, Azure, or GCP). Knowledge of data governance frameworks and metadata management. Experience with Kafka, Spark, Airflow, or similar tools for data orchestration.
Soft Skills
Strong analytical and problem-solving mindset. Excellent communication with both technical and non-technical stakeholders. Ability to thrive in a fast-paced, high-stakes trading environment.
Qualifications
Bachelor's or Master's degree in Computer Science, Finance, or related field. 5-7 years of experience in data engineering, preferably in financial services.