Role Description:
We are seeking a Senior Associate Developer (5–6 years’ experience) to join the Market Risk Technology team. You will design and build reliable Python-based data pipelines and curated datasets that support daily risk analytics. The role emphasizes hands-on delivery, data quality, performance, and collaboration with risk and business stakeholders, with ownership from planning through production and support.
Key Responsibilities:
Design and implement Market Risk data pipelines in Python—from ingestion and transformation through delivery to analytics consumers.
Own projects/features end-to-end: scope work, align with stakeholders, plan sprints, track progress, and deliver to SLAs.
Apply data quality controls (validation, reconciliation, lineage) and monitor SLAs to ensure accuracy and timeliness.
Improve performance and reliability of batch and near-real-time workflows through profiling and targeted optimization.
Translate risk/business requirements into clear technical tasks and deliver features through Agile sprints.
Automate routine workflows (packaging, testing, CI/CD, scheduling) and contribute to coding standards and reviews.
Participate in production support, assist with incident resolution, and document fixes and runbooks.
Create concise technical documentation, share knowledge with the team, and mentor junior engineers as needed.
Required Qualifications:
Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
5–6 years of hands-on Python for data processing and automation (e.g., pandas; packaging, testing).
Solid understanding of data modeling and ETL/ELT patterns; experience building maintainable pipelines.
Experience implementing data quality checks and operational monitoring aligned to accuracy/timeliness goals.
Proficiency with Git-based workflows and CI/CD; familiarity with production change management.
Demonstrated ability to take ownership of a project or feature set, coordinate across teams, and deliver on time.
Strong analytical and communication skills; collaborative approach with risk and business stakeholders.
Preferred Qualifications:
SQL skills in at least one major dialect (e.g., Oracle, SQL Server, PostgreSQL), including performance tuning.
Experience with Databricks (Python notebooks, Delta Lake/Unity Catalog) and/or PySpark.
Knowledge of cloud data platforms (e.g., AWS, Azure), including object storage (S3/ADLS) and IAM basics.
Familiarity with market risk concepts (e.g., sensitivities/Greeks, VaR, stress testing, limits, P&L decomposition).
Experience using generative AI tools for code generation, testing, and developer productivity (e.g., accelerating boilerplate, refactoring, and documentation), with appropriate engineering controls (peer review, automated testing, and secure usage practices).
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