Job Description – Cloud Data EngineerPosition
Cloud Data Engineer – Databricks / Snowflake / Azure
Experience
3+ Years
Role Overview
We are looking for a highly skilled Cloud Data Engineer to join our team for a Cloud Data Modernization initiative. The ideal candidate will have solid hands-on expertise in Databricks as the primary data platform, with Snowflake as a secondary skill, along with experience in Azure and/or AWS cloud infrastructure.
The role involves modernizing on-premises ETL workloads and migrating them to cloud-based data platforms while building scalable, secure, and high-performing data solutions.
Key Responsibilities
- Migrate and modernize on-premises ETL workloads to Azure Cloud, Databricks, and Snowflake.
- Design and implement data solutions using Azure Databricks, ADF, SHIR, Logic Apps, ADLS Gen2, Blob Storage, and Snowflake.
- Develop scalable data pipelines using Apache Spark, PySpark, Python, and SQL.
- Analyze existing on-premises ETL processes and identify opportunities for cloud modernization.
- Implement Bronze/Silver/Gold (Medallion Architecture) and Lakehouse solutions.
- Work with Delta Lake and optimize Databricks workloads for performance and scalability.
- Develop and maintain Snowflake data engineering and analytics workloads.
- Implement CI/CD and DevOps practices using GitHub Actions.
- Manage GitHub branching, pull requests, code reviews, and engineering best practices.
- Implement data quality checks, validation, reconciliation, monitoring, and observability.
- Collaborate with cross-functional teams to ensure reliable data integration and flow.
- Ensure data solutions meet required security, governance, compliance, and quality standards.
- Troubleshoot and optimize data pipelines, Databricks jobs, Spark workloads, and Snowflake processes.
- Leverage approved AI-assisted development tools such as GitHub Copilot, Databricks Assistant, ChatGPT, or Claude to improve engineering productivity.
- Work within Agile delivery
📌 Cloud Data Engineer (Noida)
🏢 UIDM
📍 Noida