Acuity Knowledge Partners
Python Developer_Data Test Engineer/ Back office(Empowering Talent: Job Opportunities for Persons with Disabilities)
Skills
13 days ago
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Important information
Contract type:
Permanent
Location:
Gurugram, Haryana, India
Work mode:
Onsite
Published on:
9 October 2026
What they need
Job Title: Python Developer _Data Test Engineer/Backoffice (Associate/ Sr Associate/ Delivery Lead/ Manager)
- Location: Gurgaon/Bangalore/Pune
- Work hours: 10am to 7pm IST
- Department: Data & Technology Services
- Experience Level : 4-10 years
Job Purpose 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 data sets, and coding standards that scale across engagements
Key Competencies
- 4–10 years of hands-on software engineering with Python (incl. packaging, virtual envs, unit/integration testing); strong use of libraries such as pandas, SQL Alchemy/ 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 or chestration; familiarity with secrets management and environment configuration.
- Domain understanding of post-trade data flows and how to encode the m into repeatable regression checks.
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