Key Skills: Databricks, Python, Spark, Kubernetes

Roles and Responsibilities:

- Design, develop, and maintain batch and near-real-time data pipelines using Apache Spark, Python, and Databricks.

- Build scalable data engineering solutions across Microsoft Azure and Google Cloud Platform environments.

- Develop data transformations, ingestion workflows, and curated datasets for reporting and analytical workloads.

- Troubleshoot data pipeline failures, improve reliability, and resolve data quality and processing issues.

- Collaborate with data architects, analytics teams, and application engineers to deliver production-grade data platforms.

Skills Required:

- 6-14 years of relevant data engineering experience.





- Strong hands-on experience with Apache Spark and Python for distributed data processing.

- Practical experience developing solutions using Databricks.

- Experience designing cloud-based data engineering solutions on Azure or Google Cloud Platform.

- Ability to develop scalable data pipelines, integrations, transformations, and analytical data stores.

Valuable to Have

- Experience with Kubernetes and containerized data workloads.

Education: B.Tech, M.Tech, BCA, or B.Sc. in Computer Science, Information Technology, Engineering, or a related discipline.

📌 Azure Data Engineer (Pune)
🏢 Careernet
📍 Pune