Python Developer

Acuity Analytics; Gurugram District; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Acuity Analytics is hiring multiple Python Developers for the AD&D team across Pune, Bengaluru and Gurgaon (hybrid: 2-3 days WFO).

We seek 4+ years of production-grade Python experience with strong SQL, data processing, and API development skills. You will build modular packages, design data flows, and implement scalable CI/CD pipelines in a hybrid work setting.

Qualifications

• 4+ years of hands-on Python software engineering, including packaging and testing.
• Strong SQL skills with experience in SQL Server/Oracle/Postgres.
• Experience with data libraries like pandas and ORM/tools (SQLAlchemy, pyodbc).
• CI/CD design and automation for code and data promotions (Azure DevOps/Jenkins/GitLab).
• Familiar with schedulers (AutoSys/Control-M/Airflow) and secret management.
• Knowledge of post-trade data flows and regression checks.

Responsibilities

• Build modular Python packages for data processing, APIs, and orchestration adapters.
• Develop backend services (FastAPI/Flask) and CLI tools with robust errors, observability, and secrets handling.
• Design and operate CI/CD pipelines for code, data, and DB objects; manage environments and rollbacks.
• Containerize services and integrate with AKS/Kubernetes; implement monitoring and alerts.
• Script batch jobs and stored procedures; translate logic into automated test scripts.

Skills

Python

SQL

Pandas

SQLAlchemy

pyodbc

asyncio

Celery

APIs

CI/CD

Git

Tools

Azure DevOps

Jenkins

GitLab

AutoSys

Control-M

Airflow

Kubernetes

SQL Server

Oracle

PostgreSQL

Job description

We are hiring multiple 'Python Developers' for our AI, Data and Digital Services (AD&D) Team at Pune, Bengaluru and Gurgaon (hybrid: 2-3 days WFO).

Immediate Joiners are highly preferred: 0-30 days - strong Python and SQL coding skills with 4+ years of production-level experience delivering reliable and scalable solutions.

What you'll do:

• Build modular Python packages (data processing, API clients, orchestration adapters), publishable to internal artifact repositories; enforce code quality, testing, and documentation standards.
• Develop backend services/APIs (e.g., FastAPI/Flask) and CLI tools to support front-end, middle-tier, and cloud workflows; implement resilient error handling, observability hooks, and secure secrets usage.

2) Data modeling, SQL & stored procedures

• Design relational schemas and write/optimize complex SQL (windowing, CTEs, partitioning); author and refactor stored procedures (SQL Server/Oracle/Postgres) with attention to edge cases and performance.
• Build data-validation utilities that compare large datasets across environments and produce diffs for regression packs.
• Map post-trade flows (allocations, clearing/settlement, confirmations, reconciliations) into datasets, rules, and assertions for repeatable regression.
• Read and translate stored-proc logic into automated test scripts; build a central repository of reusable checks integrated into CI/CD.
• Nice to have: familiarity with trade/blotter platforms (e.g., ION) or similar post-trade systems.
• Design and operate multi-stage CI/CD pipelines (Azure DevOps/Jenkins/GitLab) for code, data artifacts, and SQL deployables; implement approvals, rollbacks, environment strategy, and quality gates (lint, SAST/DAST, tests).
• Containerize services where appropriate; integrate with AKS/Kubernetes or serverless jobs and wire up metrics/alerts for runtime health.

5) Scheduling, batch & operationalization

• Script the execution of AutoSys/batch jobs and stored procedures across dev/UAT/prod; add run-books, logging, and guardrails; enable reliable, auditable promotions through environments.

What you'll bring:

• 4+ 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 orchestration; familiarity with secrets management and environment configuration.
• Domain understanding of post-trade data flows and how to encode them into repeatable regression checks.