Lead Consultant- Sr. Snowflake Data Engineer (Python+Cloud)

Python+Cloud

In this role, the Sr. Snowflake Data Engineer is responsible for providing technical direction and lead a group of one or more developer to address a goal.

• Design, develop, and optimize scalable data pipelines on Snowflake using Python and cloud-native tools.

• Build interactive, user-friendly data applications and dashboards using Streamlit to visualize AI-driven insights.

• Develop Python-based user-defined functions (UDFs) and stored procedures to enhance Snowflake processing.

• generative AI models and Cortex AI c

• Implement real-time data streaming and ingestion pipelines to support AI workloads and analytics.

• Leverage cloud platforms (AWS, Azure, GCP) for scalable data processing and seamless Snowflake integration.

• Optimize Snowflake data models and query performance to support complex AI inference workloads.

• Lead efforts in automating data workflows and model deployment pipelines with Python scripting and orchestration tools.

• Ensure data governance, security, and role-based access control (RBAC) compliance across Snowflake deployments.

• Develop prototypes and proof-of-concept applications leveraging Gen AI to demonstrate business value.

• Collaborate with stakeholders to translate AI use cases into scalable data engineering solutions.

• Mentor and lead engineering teams on best practices around Python, Snowflake, Gen AI, and Streamlit development.

• Stay current with evolving AI technologies, Snowflake enhancements, and cloud data engineering trends to drive innovation.

• Snowflake

Roles and Responsibilities:

• Requirement gathering, creating design document, providing solutions to customer, work with offshore team etc.

• Writing SQL queries against Snowflake, developing scripts to do Extract, Load, and Transform data.

• Hands-on experience with Snowflake utilities such as SnowSQL, Bulk copy, Snowpipe, Tasks, Streams, Time travel, Cloning, Optimizer, Metadata Manager, data sharing, stored procedures and UDFs, Snowsight.

• Have experience with Snowflake cloud data warehouse and AWS S3 bucket or Azure blob storage container for integrating data from multiple source system.

• Should have have some exp on AWS services (S3, Glue, Lambda) or Azure services ( Blob Storage, ADLS gen2, ADF)

• Should have good experience in Python/Pyspark.integration with Snowflake and cloud (AWS/Azure) with ability to leverage cloud services for data processing and storage.

• Proficiency in Python programming language, including knowledge of data types, variables, functions, loops, conditionals, and other Python-specific concepts.

• Knowledge of ETL (Extract, Transform, Load) processes and tools, and ability to design and develop efficient ETL jobs using Python and Pyspark.

• Should have some experience on Snowflake RBAC and data security.

• Should have good experience in implementing CDC or SCD type-2.

• Should have good experience in implementing Snowflake Best Practices

• In-depth understanding of Data Warehouse, ETL concepts and Data Modelling

• Experience in requirement gathering, analysis, designing, development, and deployment.

• Should Have experience building data ingestion pipeline

• Optimize and tune data pipelines for performance and scalability

• Able to communicate with clients and lead team.

• Proficiency in working with Airflow or other workflow management tools for scheduling and managing ETL jobs.

• Good to have experience in deployment using CI/CD tools and exp in repositories like Azure repo ,Github etc.

Qualifications we seek in you!

Minimum qualifications

• B.E./ Masters in Computer Science, Information technology, or Computer engineering or any equivalent degree with good IT experience and relevant as Senior Snowflake Data Engineer.

• Skill Metrix:

• Snowflake, Cortex AI, Python/PySpark, AWS/Azure, ETL concepts, Data Modeling & Data Warehousing concepts