Experience: 5-9 Years
Location: Noida (Work From Office)
Role Summary
We are seeking a Senior Python Software Engineer to build and maintain production-grade data platforms that operationalize data science and machine learning workflows. The role focuses on converting research prototypes into scalable, maintainable software systems, building data pipelines, APIs, and services that process and publish business-critical datasets.
You will work closely with Data Scientists to productionize analytical workflows while ensuring software engineering best practices, reliability, scalability, and maintainability.
Key Responsibilities
● Design, develop, and maintain production-grade Python applications and data pipelines.
● Convert notebook-based and Databricks workflows into modular, reusable, and testable Python services.
● Build APIs and backend services using frameworks such as Flask or FastAPI.
● Develop reliable ingestion, transformation, and publishing pipelines for structured and semi-structured data.
● Design efficient data movement across SQL and NoSQL databases.
● Build scalable solutions for processing geospatial and time-series datasets.
● Integrate third-party APIs and web data sources while handling authentication, pagination, rate limiting, and schema changes.
● Implement workflow orchestration using Airflow, Prefect, or Dagster.
● Containerize applications using Docker and deploy to AWS or GCP environments.
● Collaborate with Data Scientists to productionize ML workflows without compromising model integrity.
● Ensure code quality through testing, documentation, version control, and CI/CD practices.
Required SkillsProgramming
● Strong Python development experience (5+ years preferred)
● Object-Oriented Programming
● Clean Architecture
● Modular software design
● Unit and integration testing
Data Engineering
● Production data pipelines
● ETL/ELT development
● Data transformation
● Data validation
● Data reconciliation
Databases
● SQL
● PostgreSQL/MySQL
● MongoDB (preferred)
● Time-series or columnar databases
APIs & Backend
● Flask or FastAPI
● REST APIs
● Data ingestion services
Workflow Orchestration
● Apache Airflow
● Prefect
● Dagster
Cloud & DevOps
● Docker
● AWS or GCP
● Git
● CI/CD pipelines
Geospatial Processing
● GeoPandas
● Spatial queries
● Geohashes
● Location-based datasets
Preferred Skills
● Experience operationalizing machine learning workflows.
● Experience working with Databricks.
● Familiarity with experiment tracking.
● Understanding of data versioning and reproducibility.
● Knowledge of XGBoost, CatBoost, or LightGBM.
● Experience handling panel and time-series datasets.
● Familiarity with web scraping frameworks.
Experience
● 5–8+ years of Python software engineering experience.
● Experience building production-grade data platforms.
● Experience working alongside Data Scientists in ML-enabled products.
● Strong understanding of scalable backend architecture and distributed data systems.
Nice to Have
● Experience with ML Ops practices.
● Experience deploying AI/ML services.
● Knowledge of Kubernetes.
● Exposure to large-scale geospatial analytics.
● Familiarity with data lineage and governance tools.
What Success Looks Like
● Research notebooks are converted into production-ready services.
● Data pipelines execute reliably with minimal operational overhead.
● APIs are scalable, well-tested, and maintainable.
● Business-critical datasets are published accurately and on schedule.
Pay: From ₹80,000.00 per month
Benefits:
- Flexible schedule
- Paid sick time
- Provident Fund
- Work from home
Work Location: In person
