Dataiku/Snowflake Analyst

Job Summary:

Dataiku/Snowflake Analyst

In this role, you will be responsible for coding, testing, and delivering high quality deliverables, and should be willing to learn new technologies.

Responsibilities

• To architect and implement very large scale data intelligence solutions around Snowflake Data Warehouse
• To understand data pipelines and modern ways of automating data pipeline using cloud based Testing and clearly document implementations, so others can easily understand the requirements, implementation, and test
• Provide flexible solutions to complex business problems using our technology practices.
• Contribute to the evolution of our architecture to make it more flexible and easier to use.
• Follow our development process and guidelines
• Conduct code reviews of other developers
• Troubleshoot Production Issues
• Follow technology trends/tools and recommend improvements to our technology when appropriate.

Qualifications we seek in you!

Minimum Qualifications

BE/B Tech/MCA

Excellent written and verbal communication skills

Preferred Qualifications/ Skills

• Experience of designing and implementing a fully operational production grade large scale data solution on Snowflake Data Warehouse
• Need to have professional knowledge of AWS / Azure. Developing ETL pipelines in and out of data warehouse using combination of Python and Snowflakes SnowSQL Writing SQL queries against Snowflake
• Excellent written and verbal communication skills including presentation skill
• Hands on experience with building productionized data ingestion and processing pipelines using Java, Spark, Scala, Python
• Hands on experience designing and implementing production grade data warehousing solutions on large scale data technologies such as Teradata, Oracle or DB2 Expertise
• Understanding of technologies involved in reconstruction: backup and restoration of data and systems, database restoration.
• Will also build field enablement materials for the broader Data Analytics Technology population, to help them understand how to integrate Analytics on Data Lake on premise and cloud into customer architecture.