We’re hiring a hands-on engineer to design and build a reusable Python frameworks that spans front-end integrations, backend/middle-tier services, and cloud execution. You’ll translate complex, post-trade data flows into robust data models, stored procedures, and regression automation, and own CI/CD—including scripts to run AutoSys/batch jobs and stored procs across environments. The ideal candidate brings pragmatic engineering discipline, capital-markets data intuition, and a builder’s mindset.
Key responsibilities
Collaborate with BAs, QEs, and traders/ops to clarify requirements and co-design testable acceptance criteria; maintain living technical documentation and run-books.
Champion reusability: templates, golden pipelines, sample datasets, and coding standards that scale across engagements.
Key competencies
Must-have:
4–7 years of hands-on software engineering with Python (incl. packaging, virtual envs, unit/integration testing); strong use of libraries such as pandas, SQLAlchemy/pyodbc, and asyncio/celery for pipelines and services.
Expert SQL skills and stored-proc development (SQL Server/Oracle/Postgres), query tuning, and execution-plan analysis for large datasets.
Proven experience designing CI/CD pipelines and automating promotion (code + data + DB objects) with Azure DevOps/Jenkins/GitLab; strong Git practices and code-review hygiene.
Comfort with schedulers (AutoSys/Control-M/Airflow) and shell/Python scripting for batch orchestration; familiarity with secrets management and environment configuration.
Domain understanding of post-trade data flows and how to encode them into repeatable regression checks.
Good to have:
Cloud exposure (Azure/AWS), containers/Kubernetes, infrastructure as code (Bicep/Terraform), and DevSecOps gates (Sonar/Mend/ZAP).
Experience with capital-markets platforms (e.g., ION blotter integrations) and messaging/API patterns in trading data stacks.
Python, Pandas, SQLAlchemy, Pyodbc, Asyncio, Celery, SQL, Stored Procedures, SQL Server, Oracle, PostgreSQL, Query Tuning, Execution Plan Analysis, CI/CD, Azure DevOps, Jenkins, GitLab, Git, Code Review, AutoSys, Control-M, Airflow, Shell Scripting, Batch Orchestration, Secrets Management, Environment Configuration, Post-Trade Data Flows, Regression Testing, Unit Testing, Integration Testing, Python Packaging, Virtual Environments, Azure, AWS, Docker, Kubernetes, Bicep, Terraform, DevSecOps, SonarQube, Mend, ZAP, ION Blotter Integration, API Integration, Messaging Patterns, Data Modeling, Technical Documentation, Runbooks