1. Azure Databricks, Azure Synapse Analytics, and other Azure services.
2. - Data engineering tools like Apache Spark, Apache Kafka, and Apache Hadoop.

- - Cloud computing platforms like Azure

- - Programming languages like Python

- - Excellent communication and collaboration skills.

- - Strong problem-solving and analytical skills.

- - Ability to work in a fast-paced setting and adapt to changing requirements.

Design and Implement: Design and implement scalable, secure, and efficient data pipelines using Azure Databricks, Azure Synapse Analytics, and other relevant Azure services. Data Engineering: Develop and maintain data architectures, data models, and data governance policies to ensure data quality and integrity.

Azure Databricks: Lead the development and deployment of Azure Databricks workloads, including data ingestion,



data processing, and data visualization.

Collaboration: Collaborate with cross-functional teams, including data scientists, data analysts, and business stakeholders to understand business requirements and develop solutions.

Security and Compliance: Ensure the security and compliance of data pipelines and architectures, adhering to organizational and regulatory standards.

Troubleshooting: Troubleshoot and resolve complex technical issues related to Azure Databricks, data pipelines, and data architectures.

Mentorship: Mentor junior engineers and provide technical guidance on Azure Databricks, data engineering, and cloud computing

📌 Senior Data Engineer -4th Aug (Tues) - 6+- Kolkata - Virtual Interview
🏢 Tata Consultancy Services
📍 Kolkata