Python Data Engineer
Kyndryl · Noida · onsite · Posted 2d ago
Undisclosed4–8 yrsfulltimeSourced from
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About this role
Role Overview
What You Will Do
Required Qualifications
Preferred Qualifications
We are seeking a skilled Python Data Engineer with strong expertise in Python, Databricks, PySpark, SQL, ETL/ELT pipelines, and REST API development to support the delivery of scalable data solutions within a modern enterprise cloud environment.
In this role, you will design, develop, and maintain high-performance data pipelines and Python-based services that enable efficient data ingestion, transformation, integration, and consumption across business-critical platforms.
You will work across both data engineering and API development, leveraging Databricks and PySpark for complex data processing while building robust RESTful APIs that facilitate seamless data exchange between applications, systems, and cloud services.
The ideal candidate will possess a strong engineering mindset with a focus on scalability, automation, code quality, performance optimization, and operational excellence, ensuring reliable, secure, and production-ready solutions that support enterprise data initiatives.
What You Will Do
- Design, develop, and optimize scalable data pipelines and ETL/ELT solutions using Databricks, PySpark, Python, SQL, Delta Lake, and Medallion Architecture to support enterprise data processing and analytics.
- Build and maintain Python-based REST APIs and backend services using FastAPI, enabling secure data ingestion, integration, validation, and consumption across enterprise platforms.
- Develop and deploy cloud-native data engineering solutions on Microsoft Azure, supporting Azure Databricks, Data Lake Storage, CI/CD pipelines, automated testing, and DevOps best practices.
- Ensure engineering excellence and operational reliability through code quality, monitoring, logging, troubleshooting, performance tuning, data quality controls, and automated testing frameworks.
- Collaborate with Architects, Platform Engineers, DevOps teams, and business stakeholders to deliver secure, scalable, and high-performing data platform solutions while driving continuous improvement initiatives.
Required Qualifications
- 4-8 years of experience in Data Engineering, Python Development, or related engineering roles.
- Strong proficiency in Python, including OOP, API development, exception handling, and asynchronous programming.
- Hands-on experience with Databricks, PySpark, and SQL for developing scalable data-processing solutions.
- Proven expertise in building ETL/ELT pipelines, data transformations, and modern Lakehouse architectures.
- Experience with FastAPI, testing frameworks (pytest), and Git-based development practices.
Preferred Qualifications
- Experience with Azure Data Factory (ADF), ADLS Gen2, and Databricks Unity Catalog.
- Knowledge of Apache Airflow, Azure DevOps, and CI/CD pipeline automation.
- Familiarity with Docker, Kubernetes (AKS), Terraform, and Infrastructure as Code (IaC).
- Exposure to Kafka/Event Hubs, Azure API Management, monitoring, and data-quality frameworks.
Sourced from naukri
Skills
AutomationAzure DevopsapisApacheautomated testingAksapache airflowAdls Gen2Azure Api ManagementAnalyticsADLSAsynchronousArchitectureBondsAzure Data FactoryAzure DatabricksMicrosoft AzureAPI DevelopmentArtificial Intelligence
About Kyndryl
Kyndryl
IT Services & Consulting
23.7k+
employees
2022
4 years old
New York City, USA
US
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Kyndryl is the world's largest provider of IT infrastructure services, Kyndryl is committed to the health and continuous improvement of the vital systems at the heart of the digital economy.
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