Job highlights

- 6-14 years experience in data engineering with expertise in Apache Spark, Python, Databricks, GCP, and Azure

- Design, develop, and maintain scalable batch and streaming data pipelines; build and operationalize workloads on Databricks; implement data quality controls and collaborate with cross-functional teams

Key Skills: Python, GCP, Spark, Databricks, Azure, Bigquery

Roles and Responsibilities:

- Design, develop, and maintain scalable batch and streaming data pipelines using Apache Spark and Python.

- Build and operationalize data engineering workloads on Databricks across cloud environments.

- Develop data solutions using services and platform capabilities across Google Cloud Platform and Microsoft Azure.

- Implement data quality controls, transformation logic, error handling, and pipeline recovery mechanisms.

- Collaborate with data analysts, architects,



and application teams to deliver governed and production-ready datasets.

Skills Required:

- 6-14 years of relevant experience in data engineering and cloud data platforms.

- Strong professional experience with Apache Spark and Python for large-scale data processing.

- Hands-on experience designing and implementing solutions on Databricks.

- Practical experience with Google Cloud Platform and Microsoft Azure data environments.

- Proficiency in developing, testing, troubleshooting, and supporting production data pipelines and integrations.

Valuable to Have

- Experience with Google BigQuery for analytical data warehousing and query development.

Education: B.Tech or equivalent technical degree.

📌 Data Engineer (Pune)
🏢 Careernet
📍 Pune