Job Function Summary -
The role involves gathering and running data analytics to improve middle‑office and operational processes, identifying gaps and risks in procedures, and ensuring the accuracy of regulatory reports. The successful candidate will bring a strong technical background to develop ETL workflows, data engineering solutions, business intelligence solutions, and process re‑engineering documentation as part of the wider Operations & Middle Office organization.
The candidate will work closely with key stakeholders and senior management across departments and regions to design and implement data projects and initiatives, ensuring timely delivery. The candidate will also work in parallel with the global Operations Control team and with internal resources and external counterparties to drive continuous process improvements.
Principal Responsibilities -
Design, develop, and maintain backend services and APIs (primarily in Python) integrated with internal systems and databases.
Build and operate ETL/data pipelines to support analytics, risk controls, and regulatory/management reporting across the trade lifecycle.
Perform data extraction, transformation, and analysis using Python (pandas, NumPy) and SQL, ensuring data quality and integrity.
Generate reports on trades, positions, and exposures for internal stakeholders and regulatory requirements, maintaining accuracy and timeliness in reporting.
Automate manual reporting processes through the development of SQL/Python solutions and, where applicable, dashboards (e.g., Tableau).
Optimize and maintain databases, including query tuning, storage and capacity monitoring, naming conventions, index/schema optimization, and stored procedure reviews.
Coordinate and work closely with internal teams across Operations, IT, Legal, Compliance, and Finance globally, as well as with external parties, to deliver projects, regulatory reports, and control frameworks.
Produce daily, weekly, and monthly reporting on metrics spanning the operational trade lifecycle, including trade volumes, trade edits, matching, settlement, and positions/balances.
Qualifications/Skills Required -
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
7 - 12 years of experience in backend development and/or data engineering, preferably in financial services or capital markets.
Strong experience with Python for backend development (e.g., Django, Flask, FastAPI) and data processing (pandas, NumPy).
Advanced SQL skills, including complex queries, performance tuning, and experience with relational databases; exposure to cloud data platforms (e.g., AWS Redshift) and/or KDB is a plus.
Experience with CI/CD, Git, and automated testing; familiarity with workflow/automation tools (e.g., Alteryx, UIPath, PowerShell) is a plus.
Quick learner with strong understanding of financial products and the ability to grasp new concepts and processes quickly.
Self‑starter with solid organizational skills and the ability to multitask effectively.
Excellent written and verbal communication skills, including strong presentation skills (project plans, presentations, data mining, analysis).
Strong interpersonal skills with the ability to work collaboratively with wider teams internally as well as with external parties.
Able to prioritize in a fast‑moving, high‑pressure, constantly changing environment, with a high sense of urgency to meet tight deadlines.