Software Engineer [Data Engineer - Python, SQL, Snowflake, Cloud, Devops (CI/CD pipeline) AI (Co-pilot usage and prompt engineering/ Gen AI), Docker, Kubernetes]

We are seeking a skilled Mid-Level Data & Platform Engineer with strong expertise in Python, Snowflake, and SQL , along with foundational knowledge of DevOps, Microsoft Azure, and AI/ML concepts . The ideal candidate will be responsible for designing, developing, and maintaining data pipelines, supporting cloud-based data platforms, and contributing to automation and AI-driven initiatives. Key Responsibilities Data Engineering • Design, develop, and maintain scalable ETL/ELT pipelines using Python and SQL. • Build and optimize data models, transformations, and workflows in Snowflake. • Develop data ingestion frameworks from various structured and unstructured data sources. • Monitor and troubleshoot data pipeline failures and performance bottlenecks. • Ensure data quality, reliability, and governance standards are maintained. Snowflake & SQL • Develop and optimize complex SQL queries, stored procedures, views, and tasks. • Implement Snowflake features such as Virtual Warehouses, Streams, Tasks, and Snowpipe. • Perform query performance tuning and cost optimization. • Support data warehouse administration and security best practices. Cloud & Azure • Work with Azure services such as: • Azure Data Factory (ADF) • Azure Storage Accounts • Azure Key Vault • Azure Functions (basic) • Azure Synapse (basic exposure preferred) • Support deployment and management of cloud-native data solutions. DevOps & Automation • Utilize Git-based source control and branching strategies. • Support CI/CD pipelines using Azure DevOps or GitHub Actions. • Create deployment automation scripts and infrastructure configurations. • Participate in release management and operational support activities. AI & Emerging Technologies • Understand foundational AI/ML concepts and use cases. • Work with AI-assisted development tools (GitHub Copilot, Azure AI services, etc.). • Support integration of AI-powered features into data platforms. • Participate in proof-of-concepts involving Generative AI and data analytics. Collaboration • Collaborate with data engineers, architects, platform teams, and business stakeholders. • Participate in Agile ceremonies including sprint planning, reviews, and retrospectives. • Document technical designs, processes, and operational runbooks.