Experience in IT industry 

Working experience with building productionized data ingestion and processing data pipelines in Snowflake 

Strong understanding on Snowflake Architecture 

Fully well-versed with data warehousing concepts. 

Expertise and excellent understanding of Snowflake features and integration of Snowflake with other data processing. 

Able to create the data pipeline for ETL/ELT 

Excellent presentation and communication skills, both written and verbal Ability to problem solve and architect in an environment with unclear requirements. 

Able to create the high level and low-level design document based on requirement. 

Hands on experience in configuration, troubleshooting, testing and managing data platforms, on premises or in the cloud. 

Awareness on data visualisation tools and methodologies 

Work independently on business problems and generate meaningful insights 

Good to have some experience/knowledge on Snowpark or Streamlit or GenAI but not mandatory. 

Should have experience on implementing Snowflake Best Practices 

Snowflake SnowPro Core Certification will be added an advantage 

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, streamlit 

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.  

In-depth understanding of Data Warehouse, ETL concepts  

Experience in requirement gathering, analysis, 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. 

Good to have exp 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. 

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

Skill Metrix: 

Snowflake, Python/PySpark, AWS/Azure, ETL concepts, & Data Warehousing concepts