Job Description
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.
Desired Experience & Qualification
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.